Overview

Dataset statistics

Number of variables114
Number of observations990
Missing cells35191
Missing cells (%)31.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory705.9 KiB
Average record size in memory730.1 B

Variable types

UNSUPPORTED36
CAT36
BOOL32
NUM9
PATH1

Warnings

subreddit has constant value "990" Constant
saved has constant value "990" Constant
clicked has constant value "990" Constant
subreddit_name_prefixed has constant value "990" Constant
hidden has constant value "990" Constant
pwls has constant value "990" Constant
downs has constant value "990" Constant
hide_score has constant value "990" Constant
quarantine has constant value "990" Constant
subreddit_type has constant value "990" Constant
is_original_content has constant value "990" Constant
is_meta has constant value "990" Constant
can_mod_post has constant value "990" Constant
archived has constant value "990" Constant
is_crosspostable has constant value "990" Constant
pinned has constant value "990" Constant
media_only has constant value "990" Constant
can_gild has constant value "990" Constant
spoiler has constant value "990" Constant
locked has constant value "990" Constant
visited has constant value "990" Constant
subreddit_id has constant value "990" Constant
is_robot_indexable has constant value "990" Constant
contest_mode has constant value "990" Constant
parent_whitelist_status has constant value "990" Constant
selftext has a high cardinality: 58 distinct values High cardinality
author_fullname has a high cardinality: 525 distinct values High cardinality
thumbnail has a high cardinality: 881 distinct values High cardinality
domain has a high cardinality: 148 distinct values High cardinality
selftext_html has a high cardinality: 57 distinct values High cardinality
url_overridden_by_dest has a high cardinality: 916 distinct values High cardinality
author has a high cardinality: 526 distinct values High cardinality
url has a high cardinality: 986 distinct values High cardinality
score is highly correlated with upsHigh correlation
ups is highly correlated with scoreHigh correlation
over_18 is highly correlated with wlsHigh correlation
wls is highly correlated with over_18High correlation
subreddit_subscribers is highly correlated with created and 1 other fieldsHigh correlation
created is highly correlated with subreddit_subscribers and 1 other fieldsHigh correlation
created_utc is highly correlated with created and 1 other fieldsHigh correlation
approved_at_utc has 990 (100.0%) missing values Missing
mod_reason_title has 990 (100.0%) missing values Missing
link_flair_css_class has 452 (45.7%) missing values Missing
thumbnail_height has 96 (9.7%) missing values Missing
top_awarded_type has 990 (100.0%) missing values Missing
author_flair_background_color has 980 (99.0%) missing values Missing
thumbnail_width has 96 (9.7%) missing values Missing
author_flair_template_id has 990 (100.0%) missing values Missing
secure_media has 883 (89.2%) missing values Missing
category has 990 (100.0%) missing values Missing
link_flair_text has 449 (45.4%) missing values Missing
approved_by has 990 (100.0%) missing values Missing
author_flair_css_class has 984 (99.4%) missing values Missing
post_hint has 97 (9.8%) missing values Missing
content_categories has 990 (100.0%) missing values Missing
mod_note has 990 (100.0%) missing values Missing
crosspost_parent_list has 977 (98.7%) missing values Missing
removed_by_category has 990 (100.0%) missing values Missing
banned_by has 990 (100.0%) missing values Missing
selftext_html has 933 (94.2%) missing values Missing
likes has 990 (100.0%) missing values Missing
suggested_sort has 986 (99.6%) missing values Missing
banned_at_utc has 990 (100.0%) missing values Missing
url_overridden_by_dest has 70 (7.1%) missing values Missing
view_count has 990 (100.0%) missing values Missing
preview has 97 (9.8%) missing values Missing
link_flair_template_id has 510 (51.5%) missing values Missing
author_flair_text has 984 (99.4%) missing values Missing
removed_by has 990 (100.0%) missing values Missing
num_reports has 990 (100.0%) missing values Missing
distinguished has 988 (99.8%) missing values Missing
mod_reason_by has 990 (100.0%) missing values Missing
removal_reason has 990 (100.0%) missing values Missing
report_reasons has 990 (100.0%) missing values Missing
discussion_type has 990 (100.0%) missing values Missing
crosspost_parent has 977 (98.7%) missing values Missing
author_flair_text_color has 980 (99.0%) missing values Missing
media has 883 (89.2%) missing values Missing
author_cakeday has 988 (99.8%) missing values Missing
is_gallery has 984 (99.4%) missing values Missing
media_metadata has 983 (99.3%) missing values Missing
gallery_data has 984 (99.4%) missing values Missing
selftext_html is uniformly distributed Uniform
url_overridden_by_dest is uniformly distributed Uniform
crosspost_parent is uniformly distributed Uniform
url is uniformly distributed Uniform
title has unique values Unique
name has unique values Unique
created has unique values Unique
id has unique values Unique
permalink has unique values Unique
created_utc has unique values Unique
approved_at_utc is an unsupported type, check if it needs cleaning or further analysis Unsupported
mod_reason_title is an unsupported type, check if it needs cleaning or further analysis Unsupported
link_flair_richtext is an unsupported type, check if it needs cleaning or further analysis Unsupported
top_awarded_type is an unsupported type, check if it needs cleaning or further analysis Unsupported
media_embed is an unsupported type, check if it needs cleaning or further analysis Unsupported
author_flair_template_id is an unsupported type, check if it needs cleaning or further analysis Unsupported
user_reports is an unsupported type, check if it needs cleaning or further analysis Unsupported
secure_media is an unsupported type, check if it needs cleaning or further analysis Unsupported
category is an unsupported type, check if it needs cleaning or further analysis Unsupported
secure_media_embed is an unsupported type, check if it needs cleaning or further analysis Unsupported
approved_by is an unsupported type, check if it needs cleaning or further analysis Unsupported
edited is an unsupported type, check if it needs cleaning or further analysis Unsupported
author_flair_richtext is an unsupported type, check if it needs cleaning or further analysis Unsupported
gildings is an unsupported type, check if it needs cleaning or further analysis Unsupported
content_categories is an unsupported type, check if it needs cleaning or further analysis Unsupported
mod_note is an unsupported type, check if it needs cleaning or further analysis Unsupported
crosspost_parent_list is an unsupported type, check if it needs cleaning or further analysis Unsupported
removed_by_category is an unsupported type, check if it needs cleaning or further analysis Unsupported
banned_by is an unsupported type, check if it needs cleaning or further analysis Unsupported
likes is an unsupported type, check if it needs cleaning or further analysis Unsupported
banned_at_utc is an unsupported type, check if it needs cleaning or further analysis Unsupported
view_count is an unsupported type, check if it needs cleaning or further analysis Unsupported
preview is an unsupported type, check if it needs cleaning or further analysis Unsupported
all_awardings is an unsupported type, check if it needs cleaning or further analysis Unsupported
awarders is an unsupported type, check if it needs cleaning or further analysis Unsupported
treatment_tags is an unsupported type, check if it needs cleaning or further analysis Unsupported
removed_by is an unsupported type, check if it needs cleaning or further analysis Unsupported
num_reports is an unsupported type, check if it needs cleaning or further analysis Unsupported
mod_reason_by is an unsupported type, check if it needs cleaning or further analysis Unsupported
removal_reason is an unsupported type, check if it needs cleaning or further analysis Unsupported
report_reasons is an unsupported type, check if it needs cleaning or further analysis Unsupported
discussion_type is an unsupported type, check if it needs cleaning or further analysis Unsupported
mod_reports is an unsupported type, check if it needs cleaning or further analysis Unsupported
media is an unsupported type, check if it needs cleaning or further analysis Unsupported
media_metadata is an unsupported type, check if it needs cleaning or further analysis Unsupported
gallery_data is an unsupported type, check if it needs cleaning or further analysis Unsupported
ups has 13 (1.3%) zeros Zeros
total_awards_received has 936 (94.5%) zeros Zeros
score has 13 (1.3%) zeros Zeros
num_comments has 242 (24.4%) zeros Zeros
num_crossposts has 943 (95.3%) zeros Zeros

Reproduction

Analysis started2021-01-12 13:07:10.526527
Analysis finished2021-01-12 13:07:39.292140
Duration28.77 seconds
Software versionpandas-profiling v2.10.0
Download configurationconfig.yaml

Variables

approved_at_utc
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing990
Missing (%)100.0%
Memory size7.9 KiB

subreddit
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
democrats
990 

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters8910
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowdemocrats
2nd rowdemocrats
3rd rowdemocrats
4th rowdemocrats
5th rowdemocrats
ValueCountFrequency (%)
democrats990
100.0%
2021-01-12T21:07:39.433735image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T21:07:39.489586image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
democrats990
100.0%

Most occurring characters

ValueCountFrequency (%)
d990
11.1%
e990
11.1%
m990
11.1%
o990
11.1%
c990
11.1%
r990
11.1%
a990
11.1%
t990
11.1%
s990
11.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter8910
100.0%

Most frequent character per category

ValueCountFrequency (%)
d990
11.1%
e990
11.1%
m990
11.1%
o990
11.1%
c990
11.1%
r990
11.1%
a990
11.1%
t990
11.1%
s990
11.1%

Most occurring scripts

ValueCountFrequency (%)
Latin8910
100.0%

Most frequent character per script

ValueCountFrequency (%)
d990
11.1%
e990
11.1%
m990
11.1%
o990
11.1%
c990
11.1%
r990
11.1%
a990
11.1%
t990
11.1%
s990
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII8910
100.0%

Most frequent character per block

ValueCountFrequency (%)
d990
11.1%
e990
11.1%
m990
11.1%
o990
11.1%
c990
11.1%
r990
11.1%
a990
11.1%
t990
11.1%
s990
11.1%

selftext
Categorical

HIGH CARDINALITY

Distinct58
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
933 
[https://www.politicususa.com/2021/01/05/warnock-beats-loeffler.html](https://www.politicususa.com/2021/01/05/warnock-beats-loeffler.html)
 
1
I heard one of the hosts whisper under his breath about the Georgia senator election demographic change and I heard “well there are less white people there now” which really worries me for the part of the country that is hard right. Are people seriously that biased and racist on the right?
 
1
I am a registered Democrat, which leans toward the center. I am known for picking candidates in the primaries that are not viable by the time they get to my State. At the end of the day, I end up supporting the nominee. I have also supported Democrats in races not in my state but that is rare. However, this changes today. The certification will go ahead overnight. If the republicans have any decency and care about the Country they will drop their objections, which are not going to do anything other than pander to these criminals that broke into the Capitol. But if they do not, I pledge that I will get the list of the representatives and Senators that vote for this disgrace and will pick a dozen and support their opponents. If you are a center democrat like myself, someone to the right or a progressive. This needs a response. If you do not have money to contribute then please pledge to support the candidate nearby or work a phone bank on 2022. If you live in a deep blue state then work for candidate phone banks in other states. I know a lot of people did since I got half a dozen calls from CA and MA as I live in Florida.
 
1
Given the turmoil in DC right now, will this affect whether or not Biden will be the next president or is what the Proud Boys disrupted simply ceremonial?
 
1
Other values (53)
 
53

Length

Max length6821
Median length0
Mean length25.89191919
Min length0

Characters and Unicode

Total characters25633
Distinct characters92
Distinct categories14 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)5.8%

Sample

1st row
2nd row
3rd row
4th row
5th row
ValueCountFrequency (%)
933
94.2%
[https://www.politicususa.com/2021/01/05/warnock-beats-loeffler.html](https://www.politicususa.com/2021/01/05/warnock-beats-loeffler.html)1
 
0.1%
I heard one of the hosts whisper under his breath about the Georgia senator election demographic change and I heard “well there are less white people there now” which really worries me for the part of the country that is hard right. Are people seriously that biased and racist on the right?1
 
0.1%
I am a registered Democrat, which leans toward the center. I am known for picking candidates in the primaries that are not viable by the time they get to my State. At the end of the day, I end up supporting the nominee. I have also supported Democrats in races not in my state but that is rare. However, this changes today. The certification will go ahead overnight. If the republicans have any decency and care about the Country they will drop their objections, which are not going to do anything other than pander to these criminals that broke into the Capitol. But if they do not, I pledge that I will get the list of the representatives and Senators that vote for this disgrace and will pick a dozen and support their opponents. If you are a center democrat like myself, someone to the right or a progressive. This needs a response. If you do not have money to contribute then please pledge to support the candidate nearby or work a phone bank on 2022. If you live in a deep blue state then work for candidate phone banks in other states. I know a lot of people did since I got half a dozen calls from CA and MA as I live in Florida.1
 
0.1%
Given the turmoil in DC right now, will this affect whether or not Biden will be the next president or is what the Proud Boys disrupted simply ceremonial?1
 
0.1%
Without your(his) idiocy, the sleeping democrats who have not voted much in the past may not have woken to vote this time.1
 
0.1%
and that’s universal healthcare, a living wage, universal childcare, more access to higher education, and a progressive tax rate. Because that’s what you fucking deserve.1
 
0.1%
She deserves it for her work in Georgia this past election cycle. Her efforts in registering new voters and shedding light on voter suppression in Georgia had a large part in flipping Georgia. And she definitely deserves it more than Limbaugh1
 
0.1%
All this talk about voter fraud in Georgia isa formof voter Intimidation. The President just called out Fulton County, where Atlanta is, which is a glaring dog whistle.1
 
0.1%
Nvm, it's just privated1
 
0.1%
Other values (48)48
 
4.8%
2021-01-12T21:07:39.694039image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the226
 
5.1%
to128
 
2.9%
of105
 
2.4%
a103
 
2.3%
and102
 
2.3%
i86
 
1.9%
in77
 
1.7%
that60
 
1.4%
is49
 
1.1%
it49
 
1.1%
Other values (1402)3455
77.8%

Most occurring characters

ValueCountFrequency (%)
4334
16.9%
e2445
 
9.5%
t1831
 
7.1%
a1532
 
6.0%
o1520
 
5.9%
n1367
 
5.3%
i1357
 
5.3%
s1182
 
4.6%
r1128
 
4.4%
h1003
 
3.9%
Other values (82)7934
31.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter19386
75.6%
Space Separator4334
 
16.9%
Uppercase Letter788
 
3.1%
Other Punctuation685
 
2.7%
Decimal Number215
 
0.8%
Control128
 
0.5%
Dash Punctuation34
 
0.1%
Final Punctuation19
 
0.1%
Open Punctuation17
 
0.1%
Close Punctuation17
 
0.1%
Other values (4)10
 
< 0.1%

Most frequent character per category

ValueCountFrequency (%)
e2445
12.6%
t1831
 
9.4%
a1532
 
7.9%
o1520
 
7.8%
n1367
 
7.1%
i1357
 
7.0%
s1182
 
6.1%
r1128
 
5.8%
h1003
 
5.2%
l810
 
4.2%
Other values (16)5211
26.9%
ValueCountFrequency (%)
I144
18.3%
T81
 
10.3%
A62
 
7.9%
R56
 
7.1%
S41
 
5.2%
M41
 
5.2%
W41
 
5.2%
B40
 
5.1%
C38
 
4.8%
H32
 
4.1%
Other values (15)212
26.9%
ValueCountFrequency (%)
.259
37.8%
,178
26.0%
'86
 
12.6%
/42
 
6.1%
?29
 
4.2%
"26
 
3.8%
:16
 
2.3%
*13
 
1.9%
!9
 
1.3%
;9
 
1.3%
Other values (6)18
 
2.6%
ValueCountFrequency (%)
249
22.8%
044
20.5%
136
16.7%
517
 
7.9%
815
 
7.0%
313
 
6.0%
613
 
6.0%
711
 
5.1%
911
 
5.1%
46
 
2.8%
ValueCountFrequency (%)
18
94.7%
1
 
5.3%
ValueCountFrequency (%)
-33
97.1%
1
 
2.9%
ValueCountFrequency (%)
(13
76.5%
[4
 
23.5%
ValueCountFrequency (%)
)13
76.5%
]4
 
23.5%
ValueCountFrequency (%)
1
50.0%
1
50.0%
ValueCountFrequency (%)
4334
100.0%
ValueCountFrequency (%)
128
100.0%
ValueCountFrequency (%)
$3
100.0%
ValueCountFrequency (%)
=4
100.0%
ValueCountFrequency (%)
🌊1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin20174
78.7%
Common5459
 
21.3%

Most frequent character per script

ValueCountFrequency (%)
e2445
12.1%
t1831
 
9.1%
a1532
 
7.6%
o1520
 
7.5%
n1367
 
6.8%
i1357
 
6.7%
s1182
 
5.9%
r1128
 
5.6%
h1003
 
5.0%
l810
 
4.0%
Other values (41)5999
29.7%
ValueCountFrequency (%)
4334
79.4%
.259
 
4.7%
,178
 
3.3%
128
 
2.3%
'86
 
1.6%
249
 
0.9%
044
 
0.8%
/42
 
0.8%
136
 
0.7%
-33
 
0.6%
Other values (31)270
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII25605
99.9%
Punctuation23
 
0.1%
None5
 
< 0.1%

Most frequent character per block

ValueCountFrequency (%)
4334
16.9%
e2445
 
9.5%
t1831
 
7.2%
a1532
 
6.0%
o1520
 
5.9%
n1367
 
5.3%
i1357
 
5.3%
s1182
 
4.6%
r1128
 
4.4%
h1003
 
3.9%
Other values (74)7906
30.9%
ValueCountFrequency (%)
18
78.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
ValueCountFrequency (%)
§4
80.0%
🌊1
 
20.0%

author_fullname
Categorical

HIGH CARDINALITY

Distinct525
Distinct (%)53.2%
Missing4
Missing (%)0.4%
Memory size7.7 KiB
t2_8xm96m07
 
53
t2_yfff4
 
48
t2_612zd
 
27
t2_nkk56
 
21
t2_1vzd9pjy
 
15
Other values (520)
822 

Length

Max length11
Median length11
Mean length9.796969697
Min length3

Characters and Unicode

Total characters9699
Distinct characters37
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique401 ?
Unique (%)40.7%

Sample

1st rowt2_nkk56
2nd rowt2_4f8e5viq
3rd rowt2_17c1os
4th rowt2_yfff4
5th rowt2_2tm5mq8b
ValueCountFrequency (%)
t2_8xm96m0753
 
5.4%
t2_yfff448
 
4.8%
t2_612zd27
 
2.7%
t2_nkk5621
 
2.1%
t2_1vzd9pjy15
 
1.5%
t2_97a315
 
1.5%
t2_yj1q215
 
1.5%
t2_6n9zacfv14
 
1.4%
t2_442hlze514
 
1.4%
t2_7vedo14
 
1.4%
Other values (515)750
75.8%
2021-01-12T21:07:39.938413image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
t2_8xm96m0753
 
5.4%
t2_yfff448
 
4.8%
t2_612zd27
 
2.7%
t2_nkk5621
 
2.1%
t2_97a315
 
1.5%
t2_yj1q215
 
1.5%
t2_1vzd9pjy15
 
1.5%
t2_7vedo14
 
1.4%
t2_442hlze514
 
1.4%
t2_6n9zacfv14
 
1.4%
Other values (516)754
76.2%

Most occurring characters

ValueCountFrequency (%)
21235
 
12.7%
t1113
 
11.5%
_986
 
10.2%
1355
 
3.7%
6311
 
3.2%
5282
 
2.9%
7277
 
2.9%
f273
 
2.8%
4257
 
2.6%
9245
 
2.5%
Other values (27)4365
45.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5153
53.1%
Decimal Number3560
36.7%
Connector Punctuation986
 
10.2%

Most frequent character per category

ValueCountFrequency (%)
t1113
21.6%
f273
 
5.3%
m210
 
4.1%
z209
 
4.1%
y204
 
4.0%
k185
 
3.6%
v179
 
3.5%
j175
 
3.4%
a170
 
3.3%
d168
 
3.3%
Other values (16)2267
44.0%
ValueCountFrequency (%)
21235
34.7%
1355
 
10.0%
6311
 
8.7%
5282
 
7.9%
7277
 
7.8%
4257
 
7.2%
9245
 
6.9%
8238
 
6.7%
3199
 
5.6%
0161
 
4.5%
ValueCountFrequency (%)
_986
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5153
53.1%
Common4546
46.9%

Most frequent character per script

ValueCountFrequency (%)
t1113
21.6%
f273
 
5.3%
m210
 
4.1%
z209
 
4.1%
y204
 
4.0%
k185
 
3.6%
v179
 
3.5%
j175
 
3.4%
a170
 
3.3%
d168
 
3.3%
Other values (16)2267
44.0%
ValueCountFrequency (%)
21235
27.2%
_986
21.7%
1355
 
7.8%
6311
 
6.8%
5282
 
6.2%
7277
 
6.1%
4257
 
5.7%
9245
 
5.4%
8238
 
5.2%
3199
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII9699
100.0%

Most frequent character per block

ValueCountFrequency (%)
21235
 
12.7%
t1113
 
11.5%
_986
 
10.2%
1355
 
3.7%
6311
 
3.2%
5282
 
2.9%
7277
 
2.9%
f273
 
2.8%
4257
 
2.6%
9245
 
2.5%
Other values (27)4365
45.0%

saved
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size990.0 B
False
990 
ValueCountFrequency (%)
False990
100.0%
2021-01-12T21:07:40.009223image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

mod_reason_title
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing990
Missing (%)100.0%
Memory size7.9 KiB

gilded
Boolean

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
0
984 
1
 
6
ValueCountFrequency (%)
0984
99.4%
16
 
0.6%
2021-01-12T21:07:40.037151image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

clicked
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size990.0 B
False
990 
ValueCountFrequency (%)
False990
100.0%
2021-01-12T21:07:40.075042image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

title
Categorical

UNIQUE

Distinct990
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
Donald J. Trump on Twitter--Anarchists, Agitators or Protestors who vandalize or damage our Federal Courthouse in Portland, or any Federal Buildings in any of our Cities or States, will be prosecuted under our recently re-enacted Statues &amp; Monuments Act. MINIMUM TEN YEARS IN PRISON. Don’t do it!
 
1
West Virginia lawmaker who recorded himself storming Capitol urged to resign in petition
 
1
Thank you President Thrump for making this possible.
 
1
Uh oh
 
1
Can’t believe we made it through 2020 just to face trump zombie apocalypse smh
 
1
Other values (985)
985 

Length

Max length300
Median length58.5
Mean length70.09393939
Min length1

Characters and Unicode

Total characters69393
Distinct characters125
Distinct categories18 ?
Distinct scripts4 ?
Distinct blocks8 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique990 ?
Unique (%)100.0%

Sample

1st rowHouse Democrats launch second impeachment of Trump for his role in last week's deadly Capitol attack
2nd rowDo I have to?
3rd row"Camp Auschwitz" guy identified!
4th rowNo Crawling Back!!!
5th rowUse the 14th Amendment to ban Trump
ValueCountFrequency (%)
Donald J. Trump on Twitter--Anarchists, Agitators or Protestors who vandalize or damage our Federal Courthouse in Portland, or any Federal Buildings in any of our Cities or States, will be prosecuted under our recently re-enacted Statues &amp; Monuments Act. MINIMUM TEN YEARS IN PRISON. Don’t do it!1
 
0.1%
West Virginia lawmaker who recorded himself storming Capitol urged to resign in petition1
 
0.1%
Thank you President Thrump for making this possible.1
 
0.1%
Uh oh1
 
0.1%
Can’t believe we made it through 2020 just to face trump zombie apocalypse smh1
 
0.1%
And the winner is 👇👇1
 
0.1%
Frustration over police response to Capitol rioters vs. BLM protesters.1
 
0.1%
Latest on Capitol Hill: Explosive device found, mob roams building1
 
0.1%
Georgia On My Mind1
 
0.1%
We said we needed a revolution1
 
0.1%
Other values (980)980
99.0%
2021-01-12T21:07:40.278505image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the441
 
3.8%
to326
 
2.8%
of217
 
1.9%
trump210
 
1.8%
a183
 
1.6%
and169
 
1.5%
in152
 
1.3%
is129
 
1.1%
for127
 
1.1%
capitol126
 
1.1%
Other values (3220)9504
82.0%

Most occurring characters

ValueCountFrequency (%)
10594
15.3%
e6182
 
8.9%
t4517
 
6.5%
o4369
 
6.3%
a4009
 
5.8%
i3744
 
5.4%
r3542
 
5.1%
n3518
 
5.1%
s3465
 
5.0%
l2192
 
3.2%
Other values (115)23261
33.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter51049
73.6%
Space Separator10594
 
15.3%
Uppercase Letter5070
 
7.3%
Other Punctuation1789
 
2.6%
Decimal Number382
 
0.6%
Final Punctuation147
 
0.2%
Dash Punctuation143
 
0.2%
Close Punctuation49
 
0.1%
Open Punctuation47
 
0.1%
Initial Punctuation43
 
0.1%
Other values (8)80
 
0.1%

Most frequent character per category

ValueCountFrequency (%)
e6182
12.1%
t4517
 
8.8%
o4369
 
8.6%
a4009
 
7.9%
i3744
 
7.3%
r3542
 
6.9%
n3518
 
6.9%
s3465
 
6.8%
l2192
 
4.3%
h1978
 
3.9%
Other values (17)13533
26.5%
ValueCountFrequency (%)
T663
 
13.1%
C415
 
8.2%
S357
 
7.0%
A351
 
6.9%
I327
 
6.4%
P264
 
5.2%
R260
 
5.1%
D225
 
4.4%
W224
 
4.4%
O217
 
4.3%
Other values (16)1767
34.9%
ValueCountFrequency (%)
😂3
 
10.0%
3
 
10.0%
👇2
 
6.7%
🤷2
 
6.7%
🙏1
 
3.3%
🤮1
 
3.3%
💔1
 
3.3%
🩹1
 
3.3%
🙅1
 
3.3%
😭1
 
3.3%
Other values (14)14
46.7%
ValueCountFrequency (%)
.671
37.5%
,270
15.1%
'240
 
13.4%
!177
 
9.9%
:113
 
6.3%
?100
 
5.6%
"92
 
5.1%
/47
 
2.6%
;25
 
1.4%
*14
 
0.8%
Other values (6)40
 
2.2%
ValueCountFrequency (%)
0127
33.2%
174
19.4%
274
19.4%
529
 
7.6%
419
 
5.0%
918
 
4.7%
616
 
4.2%
711
 
2.9%
39
 
2.4%
85
 
1.3%
ValueCountFrequency (%)
-136
95.1%
5
 
3.5%
2
 
1.4%
ValueCountFrequency (%)
|18
78.3%
+4
 
17.4%
=1
 
4.3%
ValueCountFrequency (%)
23
53.5%
20
46.5%
ValueCountFrequency (%)
129
87.8%
18
 
12.2%
ValueCountFrequency (%)
)48
98.0%
]1
 
2.0%
ValueCountFrequency (%)
(46
97.9%
[1
 
2.1%
ValueCountFrequency (%)
¯2
66.7%
🏼1
33.3%
ValueCountFrequency (%)
10594
100.0%
ValueCountFrequency (%)
$10
100.0%
ValueCountFrequency (%)
4
100.0%
ValueCountFrequency (%)
4
100.0%
ValueCountFrequency (%)
_5
100.0%
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin56119
80.9%
Common13265
 
19.1%
Inherited8
 
< 0.1%
Katakana1
 
< 0.1%

Most frequent character per script

ValueCountFrequency (%)
10594
79.9%
.671
 
5.1%
,270
 
2.0%
'240
 
1.8%
!177
 
1.3%
-136
 
1.0%
129
 
1.0%
0127
 
1.0%
:113
 
0.9%
?100
 
0.8%
Other values (59)708
 
5.3%
ValueCountFrequency (%)
e6182
 
11.0%
t4517
 
8.0%
o4369
 
7.8%
a4009
 
7.1%
i3744
 
6.7%
r3542
 
6.3%
n3518
 
6.3%
s3465
 
6.2%
l2192
 
3.9%
h1978
 
3.5%
Other values (43)18603
33.1%
ValueCountFrequency (%)
4
50.0%
4
50.0%
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII69142
99.6%
Punctuation212
 
0.3%
None19
 
< 0.1%
Emoticons9
 
< 0.1%
Misc Symbols4
 
< 0.1%
VS4
 
< 0.1%
Enclosed Alphanum Sup2
 
< 0.1%
Katakana1
 
< 0.1%

Most frequent character per block

ValueCountFrequency (%)
10594
15.3%
e6182
 
8.9%
t4517
 
6.5%
o4369
 
6.3%
a4009
 
5.8%
i3744
 
5.4%
r3542
 
5.1%
n3518
 
5.1%
s3465
 
5.0%
l2192
 
3.2%
Other values (78)23010
33.3%
ValueCountFrequency (%)
129
60.8%
23
 
10.8%
20
 
9.4%
18
 
8.5%
11
 
5.2%
5
 
2.4%
4
 
1.9%
2
 
0.9%
ValueCountFrequency (%)
😂3
33.3%
🙏1
 
11.1%
🙅1
 
11.1%
😭1
 
11.1%
😏1
 
11.1%
😒1
 
11.1%
🙄1
 
11.1%
ValueCountFrequency (%)
👇2
 
10.5%
🤷2
 
10.5%
¯2
 
10.5%
ú1
 
5.3%
🤮1
 
5.3%
💔1
 
5.3%
🩹1
 
5.3%
🤣1
 
5.3%
🤡1
 
5.3%
🍑1
 
5.3%
Other values (6)6
31.6%
ValueCountFrequency (%)
3
75.0%
1
 
25.0%
ValueCountFrequency (%)
4
100.0%
ValueCountFrequency (%)
1
100.0%
ValueCountFrequency (%)
🇺1
50.0%
🇸1
50.0%

link_flair_richtext
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size7.9 KiB

subreddit_name_prefixed
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
r/democrats
990 

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters10890
Distinct characters10
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowr/democrats
2nd rowr/democrats
3rd rowr/democrats
4th rowr/democrats
5th rowr/democrats
ValueCountFrequency (%)
r/democrats990
100.0%
2021-01-12T21:07:40.474977image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T21:07:40.533822image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
r/democrats990
100.0%

Most occurring characters

ValueCountFrequency (%)
r1980
18.2%
/990
9.1%
d990
9.1%
e990
9.1%
m990
9.1%
o990
9.1%
c990
9.1%
a990
9.1%
t990
9.1%
s990
9.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter9900
90.9%
Other Punctuation990
 
9.1%

Most frequent character per category

ValueCountFrequency (%)
r1980
20.0%
d990
10.0%
e990
10.0%
m990
10.0%
o990
10.0%
c990
10.0%
a990
10.0%
t990
10.0%
s990
10.0%
ValueCountFrequency (%)
/990
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin9900
90.9%
Common990
 
9.1%

Most frequent character per script

ValueCountFrequency (%)
r1980
20.0%
d990
10.0%
e990
10.0%
m990
10.0%
o990
10.0%
c990
10.0%
a990
10.0%
t990
10.0%
s990
10.0%
ValueCountFrequency (%)
/990
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII10890
100.0%

Most frequent character per block

ValueCountFrequency (%)
r1980
18.2%
/990
9.1%
d990
9.1%
e990
9.1%
m990
9.1%
o990
9.1%
c990
9.1%
a990
9.1%
t990
9.1%
s990
9.1%

hidden
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size990.0 B
False
990 
ValueCountFrequency (%)
False990
100.0%
2021-01-12T21:07:40.562742image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

pwls
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
6
990 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters990
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row6
2nd row6
3rd row6
4th row6
5th row6
ValueCountFrequency (%)
6990
100.0%
2021-01-12T21:07:40.702368image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T21:07:40.756224image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
6990
100.0%

Most occurring characters

ValueCountFrequency (%)
6990
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number990
100.0%

Most frequent character per category

ValueCountFrequency (%)
6990
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common990
100.0%

Most frequent character per script

ValueCountFrequency (%)
6990
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII990
100.0%

Most frequent character per block

ValueCountFrequency (%)
6990
100.0%

link_flair_css_class
Categorical

MISSING

Distinct2
Distinct (%)0.4%
Missing452
Missing (%)45.7%
Memory size7.7 KiB
480 
blue
58 

Length

Max length4
Median length3
Mean length1.604040404
Min length0

Characters and Unicode

Total characters1588
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd rownan
3rd rownan
4th row
5th row
ValueCountFrequency (%)
480
48.5%
blue58
 
5.9%
(Missing)452
45.7%
2021-01-12T21:07:40.902832image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T21:07:40.970655image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
nan452
88.6%
blue58
 
11.4%

Most occurring characters

ValueCountFrequency (%)
n904
56.9%
a452
28.5%
b58
 
3.7%
l58
 
3.7%
u58
 
3.7%
e58
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1588
100.0%

Most frequent character per category

ValueCountFrequency (%)
n904
56.9%
a452
28.5%
b58
 
3.7%
l58
 
3.7%
u58
 
3.7%
e58
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
Latin1588
100.0%

Most frequent character per script

ValueCountFrequency (%)
n904
56.9%
a452
28.5%
b58
 
3.7%
l58
 
3.7%
u58
 
3.7%
e58
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII1588
100.0%

Most frequent character per block

ValueCountFrequency (%)
n904
56.9%
a452
28.5%
b58
 
3.7%
l58
 
3.7%
u58
 
3.7%
e58
 
3.7%

downs
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
0
990 
ValueCountFrequency (%)
0990
100.0%
2021-01-12T21:07:41.007526image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

thumbnail_height
Real number (ℝ≥0)

MISSING

Distinct80
Distinct (%)8.9%
Missing96
Missing (%)9.7%
Infinite0
Infinite (%)0.0%
Mean101.163311
Minimum31
Maximum140
Zeros0
Zeros (%)0.0%
Memory size7.7 KiB
2021-01-12T21:07:41.071380image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum31
5-th percentile72
Q178
median93
Q3139
95-th percentile140
Maximum140
Range109
Interquartile range (IQR)61

Descriptive statistics

Standard deviation26.70183247
Coefficient of variation (CV)0.2639477911
Kurtosis-1.184027931
Mean101.163311
Median Absolute Deviation (MAD)15
Skewness0.3632411842
Sum90440
Variance712.9878573
MonotocityNot monotonic
2021-01-12T21:07:41.181089image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
140221
22.3%
78179
18.1%
10590
9.1%
9389
9.0%
7372
 
7.3%
7011
 
1.1%
9210
 
1.0%
7210
 
1.0%
948
 
0.8%
797
 
0.7%
Other values (70)197
19.9%
(Missing)96
9.7%
ValueCountFrequency (%)
311
0.1%
351
0.1%
381
0.1%
391
0.1%
411
0.1%
ValueCountFrequency (%)
140221
22.3%
1394
 
0.4%
1382
 
0.2%
1364
 
0.4%
1356
 
0.6%

top_awarded_type
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing990
Missing (%)100.0%
Memory size7.9 KiB

hide_score
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size990.0 B
False
990 
ValueCountFrequency (%)
False990
100.0%
2021-01-12T21:07:41.253894image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

name
Categorical

UNIQUE

Distinct990
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
t3_kqkswb
 
1
t3_krzlgb
 
1
t3_kssqhr
 
1
t3_ktd7xk
 
1
t3_ks2vo4
 
1
Other values (985)
985 

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters8910
Distinct characters37
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique990 ?
Unique (%)100.0%

Sample

1st rowt3_kv4lr7
2nd rowt3_kvg3xu
3rd rowt3_kv4oca
4th rowt3_kvekkt
5th rowt3_kvfqwa
ValueCountFrequency (%)
t3_kqkswb1
 
0.1%
t3_krzlgb1
 
0.1%
t3_kssqhr1
 
0.1%
t3_ktd7xk1
 
0.1%
t3_ks2vo41
 
0.1%
t3_kru3f21
 
0.1%
t3_kv6i5q1
 
0.1%
t3_kvhzy81
 
0.1%
t3_krvyex1
 
0.1%
t3_ksxsht1
 
0.1%
Other values (980)980
99.0%
2021-01-12T21:07:41.430421image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
t3_kqkswb1
 
0.1%
t3_krzlgb1
 
0.1%
t3_kssqhr1
 
0.1%
t3_ktd7xk1
 
0.1%
t3_ks2vo41
 
0.1%
t3_kru3f21
 
0.1%
t3_kv6i5q1
 
0.1%
t3_kvhzy81
 
0.1%
t3_krvyex1
 
0.1%
t3_ksxsht1
 
0.1%
Other values (980)980
99.0%

Most occurring characters

ValueCountFrequency (%)
t1283
14.4%
k1097
 
12.3%
31090
 
12.2%
_990
 
11.1%
r358
 
4.0%
s349
 
3.9%
u252
 
2.8%
v220
 
2.5%
q168
 
1.9%
y131
 
1.5%
Other values (27)2972
33.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5851
65.7%
Decimal Number2069
 
23.2%
Connector Punctuation990
 
11.1%

Most frequent character per category

ValueCountFrequency (%)
t1283
21.9%
k1097
18.7%
r358
 
6.1%
s349
 
6.0%
u252
 
4.3%
v220
 
3.8%
q168
 
2.9%
y131
 
2.2%
z130
 
2.2%
f128
 
2.2%
Other values (16)1735
29.7%
ValueCountFrequency (%)
31090
52.7%
4128
 
6.2%
5117
 
5.7%
0114
 
5.5%
8112
 
5.4%
1112
 
5.4%
7110
 
5.3%
9106
 
5.1%
299
 
4.8%
681
 
3.9%
ValueCountFrequency (%)
_990
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5851
65.7%
Common3059
34.3%

Most frequent character per script

ValueCountFrequency (%)
t1283
21.9%
k1097
18.7%
r358
 
6.1%
s349
 
6.0%
u252
 
4.3%
v220
 
3.8%
q168
 
2.9%
y131
 
2.2%
z130
 
2.2%
f128
 
2.2%
Other values (16)1735
29.7%
ValueCountFrequency (%)
31090
35.6%
_990
32.4%
4128
 
4.2%
5117
 
3.8%
0114
 
3.7%
8112
 
3.7%
1112
 
3.7%
7110
 
3.6%
9106
 
3.5%
299
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII8910
100.0%

Most frequent character per block

ValueCountFrequency (%)
t1283
14.4%
k1097
 
12.3%
31090
 
12.2%
_990
 
11.1%
r358
 
4.0%
s349
 
3.9%
u252
 
2.8%
v220
 
2.5%
q168
 
1.9%
y131
 
1.5%
Other values (27)2972
33.4%

quarantine
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size990.0 B
False
990 
ValueCountFrequency (%)
False990
100.0%
2021-01-12T21:07:41.488273image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
dark
593 
light
397 

Length

Max length5
Median length4
Mean length4.401010101
Min length4

Characters and Unicode

Total characters4357
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowdark
2nd rowdark
3rd rowdark
4th rowdark
5th rowlight
ValueCountFrequency (%)
dark593
59.9%
light397
40.1%
2021-01-12T21:07:41.655383image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T21:07:41.717217image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
dark593
59.9%
light397
40.1%

Most occurring characters

ValueCountFrequency (%)
d593
13.6%
a593
13.6%
r593
13.6%
k593
13.6%
l397
9.1%
i397
9.1%
g397
9.1%
h397
9.1%
t397
9.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4357
100.0%

Most frequent character per category

ValueCountFrequency (%)
d593
13.6%
a593
13.6%
r593
13.6%
k593
13.6%
l397
9.1%
i397
9.1%
g397
9.1%
h397
9.1%
t397
9.1%

Most occurring scripts

ValueCountFrequency (%)
Latin4357
100.0%

Most frequent character per script

ValueCountFrequency (%)
d593
13.6%
a593
13.6%
r593
13.6%
k593
13.6%
l397
9.1%
i397
9.1%
g397
9.1%
h397
9.1%
t397
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII4357
100.0%

Most frequent character per block

ValueCountFrequency (%)
d593
13.6%
a593
13.6%
r593
13.6%
k593
13.6%
l397
9.1%
i397
9.1%
g397
9.1%
h397
9.1%
t397
9.1%

upvote_ratio
Real number (ℝ≥0)

Distinct53
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.8589393939
Minimum0.27
Maximum1
Zeros0
Zeros (%)0.0%
Memory size7.7 KiB
2021-01-12T21:07:41.793014image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0.27
5-th percentile0.6445
Q10.81
median0.88
Q30.94
95-th percentile0.98
Maximum1
Range0.73
Interquartile range (IQR)0.13

Descriptive statistics

Standard deviation0.1086147093
Coefficient of variation (CV)0.1264521223
Kurtosis2.630048387
Mean0.8589393939
Median Absolute Deviation (MAD)0.07
Skewness-1.372771794
Sum850.35
Variance0.01179715507
MonotocityNot monotonic
2021-01-12T21:07:41.902749image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.9757
 
5.8%
0.9655
 
5.6%
0.9453
 
5.4%
0.8747
 
4.7%
0.9245
 
4.5%
0.942
 
4.2%
0.9541
 
4.1%
0.9340
 
4.0%
0.8940
 
4.0%
0.8539
 
3.9%
Other values (43)531
53.6%
ValueCountFrequency (%)
0.271
0.1%
0.331
0.1%
0.41
0.1%
0.421
0.1%
0.431
0.1%
ValueCountFrequency (%)
137
3.7%
0.999
 
0.9%
0.9826
2.6%
0.9757
5.8%
0.9655
5.6%
Distinct1
Distinct (%)10.0%
Missing980
Missing (%)99.0%
Memory size7.7 KiB
10 

Length

Max length3
Median length3
Mean length2.96969697
Min length0

Characters and Unicode

Total characters2940
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rownan
2nd rownan
3rd rownan
4th rownan
5th rownan
ValueCountFrequency (%)
10
 
1.0%
(Missing)980
99.0%
2021-01-12T21:07:42.100224image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T21:07:42.161056image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
nan980
100.0%

Most occurring characters

ValueCountFrequency (%)
n1960
66.7%
a980
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2940
100.0%

Most frequent character per category

ValueCountFrequency (%)
n1960
66.7%
a980
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2940
100.0%

Most frequent character per script

ValueCountFrequency (%)
n1960
66.7%
a980
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII2940
100.0%

Most frequent character per block

ValueCountFrequency (%)
n1960
66.7%
a980
33.3%

subreddit_type
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
public
990 

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters5940
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowpublic
2nd rowpublic
3rd rowpublic
4th rowpublic
5th rowpublic
ValueCountFrequency (%)
public990
100.0%
2021-01-12T21:07:42.301653image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T21:07:42.359526image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
public990
100.0%

Most occurring characters

ValueCountFrequency (%)
p990
16.7%
u990
16.7%
b990
16.7%
l990
16.7%
i990
16.7%
c990
16.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5940
100.0%

Most frequent character per category

ValueCountFrequency (%)
p990
16.7%
u990
16.7%
b990
16.7%
l990
16.7%
i990
16.7%
c990
16.7%

Most occurring scripts

ValueCountFrequency (%)
Latin5940
100.0%

Most frequent character per script

ValueCountFrequency (%)
p990
16.7%
u990
16.7%
b990
16.7%
l990
16.7%
i990
16.7%
c990
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII5940
100.0%

Most frequent character per block

ValueCountFrequency (%)
p990
16.7%
u990
16.7%
b990
16.7%
l990
16.7%
i990
16.7%
c990
16.7%

ups
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct168
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean97.02929293
Minimum0
Maximum6376
Zeros13
Zeros (%)1.3%
Memory size7.7 KiB
2021-01-12T21:07:42.588907image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.45
Q18
median15
Q335.75
95-th percentile197.55
Maximum6376
Range6376
Interquartile range (IQR)27.75

Descriptive statistics

Standard deviation476.4863649
Coefficient of variation (CV)4.910747575
Kurtosis88.74509507
Mean97.02929293
Median Absolute Deviation (MAD)9
Skewness8.941137474
Sum96059
Variance227039.256
MonotocityNot monotonic
2021-01-12T21:07:42.690641image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
546
 
4.6%
1042
 
4.2%
640
 
4.0%
740
 
4.0%
1437
 
3.7%
936
 
3.6%
1135
 
3.5%
835
 
3.5%
1233
 
3.3%
333
 
3.3%
Other values (158)613
61.9%
ValueCountFrequency (%)
013
 
1.3%
117
1.7%
220
2.0%
333
3.3%
428
2.8%
ValueCountFrequency (%)
63761
0.1%
56011
0.1%
51081
0.1%
45371
0.1%
43391
0.1%

total_awards_received
Real number (ℝ≥0)

ZEROS

Distinct10
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1222222222
Minimum0
Maximum13
Zeros936
Zeros (%)94.5%
Memory size7.7 KiB
2021-01-12T21:07:42.782395image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum13
Range13
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.7957236
Coefficient of variation (CV)6.510465818
Kurtosis151.6404542
Mean0.1222222222
Median Absolute Deviation (MAD)0
Skewness11.2402133
Sum121
Variance0.6331760476
MonotocityNot monotonic
2021-01-12T21:07:42.867168image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0936
94.5%
135
 
3.5%
27
 
0.7%
44
 
0.4%
33
 
0.3%
131
 
0.1%
121
 
0.1%
101
 
0.1%
71
 
0.1%
51
 
0.1%
ValueCountFrequency (%)
0936
94.5%
135
 
3.5%
27
 
0.7%
33
 
0.3%
44
 
0.4%
ValueCountFrequency (%)
131
0.1%
121
0.1%
101
0.1%
71
0.1%
51
0.1%

media_embed
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size7.9 KiB

thumbnail_width
Categorical

MISSING

Distinct2
Distinct (%)0.2%
Missing96
Missing (%)9.7%
Memory size7.7 KiB
140
893 
70
 
1

Length

Max length5
Median length5
Mean length4.805050505
Min length3

Characters and Unicode

Total characters4757
Distinct characters7
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rownan
2nd row140.0
3rd row140.0
4th row140.0
5th row140.0
ValueCountFrequency (%)
140893
90.2%
701
 
0.1%
(Missing)96
 
9.7%
2021-01-12T21:07:43.043668image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T21:07:43.110517image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
140.0893
90.2%
nan96
 
9.7%
70.01
 
0.1%

Most occurring characters

ValueCountFrequency (%)
01788
37.6%
.894
18.8%
1893
18.8%
4893
18.8%
n192
 
4.0%
a96
 
2.0%
71
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number3575
75.2%
Other Punctuation894
 
18.8%
Lowercase Letter288
 
6.1%

Most frequent character per category

ValueCountFrequency (%)
01788
50.0%
1893
25.0%
4893
25.0%
71
 
< 0.1%
ValueCountFrequency (%)
n192
66.7%
a96
33.3%
ValueCountFrequency (%)
.894
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common4469
93.9%
Latin288
 
6.1%

Most frequent character per script

ValueCountFrequency (%)
01788
40.0%
.894
20.0%
1893
20.0%
4893
20.0%
71
 
< 0.1%
ValueCountFrequency (%)
n192
66.7%
a96
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII4757
100.0%

Most frequent character per block

ValueCountFrequency (%)
01788
37.6%
.894
18.8%
1893
18.8%
4893
18.8%
n192
 
4.0%
a96
 
2.0%
71
 
< 0.1%

author_flair_template_id
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing990
Missing (%)100.0%
Memory size7.9 KiB

is_original_content
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size990.0 B
False
990 
ValueCountFrequency (%)
False990
100.0%
2021-01-12T21:07:43.148415image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

user_reports
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size7.9 KiB

secure_media
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing883
Missing (%)89.2%
Memory size7.9 KiB
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size990.0 B
False
567 
True
423 
ValueCountFrequency (%)
False567
57.3%
True423
42.7%
2021-01-12T21:07:43.177339image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

is_meta
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size990.0 B
False
990 
ValueCountFrequency (%)
False990
100.0%
2021-01-12T21:07:43.214241image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

category
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing990
Missing (%)100.0%
Memory size7.9 KiB

secure_media_embed
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size7.9 KiB

link_flair_text
Categorical

MISSING

Distinct25
Distinct (%)4.6%
Missing449
Missing (%)45.4%
Memory size7.7 KiB
:snoo: Article
94 
🗳️ Beat Trump
79 
:snoo_joy: Meme
70 
article
58 
:snoo_smile: Humor
46 
Other values (20)
194 

Length

Max length48
Median length7
Mean length10.52020202
Min length3

Characters and Unicode

Total characters10415
Distinct characters51
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)0.7%

Sample

1st row🔴 Megathread
2nd rownan
3rd rownan
4th row📄Effortpost
5th row🗳️ Beat Trump
ValueCountFrequency (%)
:snoo: Article 94
 
9.5%
🗳️ Beat Trump79
 
8.0%
:snoo_joy: Meme70
 
7.1%
article58
 
5.9%
:snoo_smile: Humor46
 
4.6%
📺 Video43
 
4.3%
:snoo_feelsgoodman: Discussion :snoo_thoughtful:37
 
3.7%
:snoo_putback: Opinion26
 
2.6%
:snoo_smile: Satire17
 
1.7%
Question :snoo_thoughtful:13
 
1.3%
Other values (15)58
 
5.9%
(Missing)449
45.4%
2021-01-12T21:07:43.371850image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan449
28.5%
article152
 
9.6%
snoo94
 
6.0%
beat79
 
5.0%
trump79
 
5.0%
🗳️79
 
5.0%
snoo_joy70
 
4.4%
meme70
 
4.4%
snoo_smile63
 
4.0%
snoo_thoughtful55
 
3.5%
Other values (30)386
24.5%

Most occurring characters

ValueCountFrequency (%)
n1451
13.9%
o1180
 
11.3%
:732
 
7.0%
a714
 
6.9%
681
 
6.5%
e675
 
6.5%
s636
 
6.1%
i450
 
4.3%
t449
 
4.3%
r356
 
3.4%
Other values (41)3091
29.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7942
76.3%
Other Punctuation732
 
7.0%
Space Separator681
 
6.5%
Uppercase Letter567
 
5.4%
Connector Punctuation265
 
2.5%
Other Symbol149
 
1.4%
Nonspacing Mark79
 
0.8%

Most frequent character per category

ValueCountFrequency (%)
n1451
18.3%
o1180
14.9%
a714
9.0%
e675
8.5%
s636
8.0%
i450
 
5.7%
t449
 
5.7%
r356
 
4.5%
u333
 
4.2%
l326
 
4.1%
Other values (13)1372
17.3%
ValueCountFrequency (%)
A95
16.8%
B81
14.3%
T79
13.9%
M73
12.9%
H46
8.1%
V43
7.6%
D37
 
6.5%
O27
 
4.8%
S26
 
4.6%
E20
 
3.5%
Other values (5)40
7.1%
ValueCountFrequency (%)
🗳79
53.0%
📺43
28.9%
📄9
 
6.0%
8
 
5.4%
🔴3
 
2.0%
📰2
 
1.3%
📉2
 
1.3%
📊2
 
1.3%
💬1
 
0.7%
ValueCountFrequency (%)
681
100.0%
ValueCountFrequency (%)
79
100.0%
ValueCountFrequency (%)
:732
100.0%
ValueCountFrequency (%)
_265
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8509
81.7%
Common1827
 
17.5%
Inherited79
 
0.8%

Most frequent character per script

ValueCountFrequency (%)
n1451
17.1%
o1180
13.9%
a714
 
8.4%
e675
 
7.9%
s636
 
7.5%
i450
 
5.3%
t449
 
5.3%
r356
 
4.2%
u333
 
3.9%
l326
 
3.8%
Other values (28)1939
22.8%
ValueCountFrequency (%)
:732
40.1%
681
37.3%
_265
 
14.5%
🗳79
 
4.3%
📺43
 
2.4%
📄9
 
0.5%
8
 
0.4%
🔴3
 
0.2%
📰2
 
0.1%
📉2
 
0.1%
Other values (2)3
 
0.2%
ValueCountFrequency (%)
79
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII10187
97.8%
None141
 
1.4%
VS79
 
0.8%
Dingbats8
 
0.1%

Most frequent character per block

ValueCountFrequency (%)
🗳79
56.0%
📺43
30.5%
📄9
 
6.4%
🔴3
 
2.1%
📰2
 
1.4%
📉2
 
1.4%
📊2
 
1.4%
💬1
 
0.7%
ValueCountFrequency (%)
n1451
14.2%
o1180
11.6%
:732
 
7.2%
a714
 
7.0%
681
 
6.7%
e675
 
6.6%
s636
 
6.2%
i450
 
4.4%
t449
 
4.4%
r356
 
3.5%
Other values (31)2863
28.1%
ValueCountFrequency (%)
79
100.0%
ValueCountFrequency (%)
8
100.0%

can_mod_post
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size990.0 B
False
990 
ValueCountFrequency (%)
False990
100.0%
2021-01-12T21:07:43.430700image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

score
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct168
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean97.02929293
Minimum0
Maximum6376
Zeros13
Zeros (%)1.3%
Memory size7.7 KiB
2021-01-12T21:07:43.493089image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.45
Q18
median15
Q335.75
95-th percentile197.55
Maximum6376
Range6376
Interquartile range (IQR)27.75

Descriptive statistics

Standard deviation476.4863649
Coefficient of variation (CV)4.910747575
Kurtosis88.74509507
Mean97.02929293
Median Absolute Deviation (MAD)9
Skewness8.941137474
Sum96059
Variance227039.256
MonotocityNot monotonic
2021-01-12T21:07:43.591824image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
546
 
4.6%
1042
 
4.2%
640
 
4.0%
740
 
4.0%
1437
 
3.7%
936
 
3.6%
1135
 
3.5%
835
 
3.5%
1233
 
3.3%
333
 
3.3%
Other values (158)613
61.9%
ValueCountFrequency (%)
013
 
1.3%
117
1.7%
220
2.0%
333
3.3%
428
2.8%
ValueCountFrequency (%)
63761
0.1%
56011
0.1%
51081
0.1%
45371
0.1%
43391
0.1%

approved_by
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing990
Missing (%)100.0%
Memory size7.9 KiB
Distinct2
Distinct (%)0.2%
Missing4
Missing (%)0.4%
Memory size7.7 KiB
False
698 
True
288 
(Missing)
 
4
ValueCountFrequency (%)
False698
70.5%
True288
29.1%
(Missing)4
 
0.4%
2021-01-12T21:07:43.668593image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

thumbnail
Categorical

HIGH CARDINALITY

Distinct881
Distinct (%)89.0%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
self
 
69
default
 
27
nsfw
 
10
https://b.thumbs.redditmedia.com/9Uys507Nv1qOzdFiEMP2CfnmhtudbYTfbqUu8H5Q8wc.jpg
 
2
https://b.thumbs.redditmedia.com/ETTVsydDvB3MRjNVWt7_deJdrEHHSoCQ2OACBZlOcsE.jpg
 
2
Other values (876)
880 

Length

Max length80
Median length80
Mean length71.94444444
Min length4

Characters and Unicode

Total characters71225
Distinct characters67
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique872 ?
Unique (%)88.1%

Sample

1st rowdefault
2nd rowhttps://b.thumbs.redditmedia.com/M36F25Qpk1BhfFggn_BTDeKt1uBhlc1PPDUjpbGUGSg.jpg
3rd rowhttps://b.thumbs.redditmedia.com/zV6srycz20pOs5oTC-OJA8ZB775smAhjKA37Z92diAg.jpg
4th rowhttps://b.thumbs.redditmedia.com/9-aJH-bi1cSYsH3t_1SPCYfAWfYguWlTj4Cjd-uvuUw.jpg
5th rowhttps://b.thumbs.redditmedia.com/vwXKKbri_gr3sZc5k1BzCQBGPFkxbk6M81UHqf1CG9o.jpg
ValueCountFrequency (%)
self69
 
7.0%
default27
 
2.7%
nsfw10
 
1.0%
https://b.thumbs.redditmedia.com/9Uys507Nv1qOzdFiEMP2CfnmhtudbYTfbqUu8H5Q8wc.jpg2
 
0.2%
https://b.thumbs.redditmedia.com/ETTVsydDvB3MRjNVWt7_deJdrEHHSoCQ2OACBZlOcsE.jpg2
 
0.2%
https://b.thumbs.redditmedia.com/JDD58YQ254Bq91GGrNLfzBKMfoouuSnwLwtvFY4zBfc.jpg2
 
0.2%
https://b.thumbs.redditmedia.com/P7UFAz2qqWCPY6Tagcdt26AWQ1tA4u9JIlcfe4DWXsQ.jpg2
 
0.2%
https://b.thumbs.redditmedia.com/yNzaBG6QME42rqbLKLRrbQygmiwIyAmMGSBrvyVI4vs.jpg2
 
0.2%
https://b.thumbs.redditmedia.com/cqETkZBxhD93iaH3VpX2P17xp6sDBOpDu3DA9JYCYzg.jpg2
 
0.2%
https://b.thumbs.redditmedia.com/Hof5eMtYYfBddxEyCE2BlWN0bTyhmM2x9CeaiqE9-bE.jpg1
 
0.1%
Other values (871)871
88.0%
2021-01-12T21:07:43.875068image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
self69
 
7.0%
default27
 
2.7%
nsfw10
 
1.0%
https://b.thumbs.redditmedia.com/ettvsyddvb3mrjnvwt7_dejdrehhsocq2oacbzlocse.jpg2
 
0.2%
https://b.thumbs.redditmedia.com/ynzabg6qme42rqblklrrbqygmiwiyammgsbrvyvi4vs.jpg2
 
0.2%
https://b.thumbs.redditmedia.com/9uys507nv1qozdfiemp2cfnmhtudbytfbquu8h5q8wc.jpg2
 
0.2%
https://b.thumbs.redditmedia.com/jdd58yq254bq91ggrnlfzbkmfoouusnwlwtvfy4zbfc.jpg2
 
0.2%
https://b.thumbs.redditmedia.com/cqetkzbxhd93iah3vpx2p17xp6sdbopdu3da9jycyzg.jpg2
 
0.2%
https://b.thumbs.redditmedia.com/p7ufaz2qqwcpy6tagcdt26awq1ta4u9jilcfe4dwxsq.jpg2
 
0.2%
https://b.thumbs.redditmedia.com/p8rxpqgzzqwq7wa43n1akuzrva87kz57dtovo-1mlbs.jpg1
 
0.1%
Other values (871)871
88.0%

Most occurring characters

ValueCountFrequency (%)
t4108
 
5.8%
.3536
 
5.0%
m3264
 
4.6%
d3236
 
4.5%
/2652
 
3.7%
s2442
 
3.4%
e2436
 
3.4%
h2364
 
3.3%
i2346
 
3.3%
p2320
 
3.3%
Other values (57)42521
59.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter41474
58.2%
Uppercase Letter15455
 
21.7%
Other Punctuation7072
 
9.9%
Decimal Number6080
 
8.5%
Dash Punctuation586
 
0.8%
Connector Punctuation558
 
0.8%

Most frequent character per category

ValueCountFrequency (%)
t4108
 
9.9%
m3264
 
7.9%
d3236
 
7.8%
s2442
 
5.9%
e2436
 
5.9%
h2364
 
5.7%
i2346
 
5.7%
p2320
 
5.6%
b2174
 
5.2%
a1662
 
4.0%
Other values (16)15122
36.5%
ValueCountFrequency (%)
A687
 
4.4%
E648
 
4.2%
I639
 
4.1%
M622
 
4.0%
B617
 
4.0%
Q612
 
4.0%
C612
 
4.0%
U611
 
4.0%
L598
 
3.9%
K591
 
3.8%
Other values (16)9218
59.6%
ValueCountFrequency (%)
8649
10.7%
0643
10.6%
7631
10.4%
4603
9.9%
5601
9.9%
9601
9.9%
2596
9.8%
6591
9.7%
3586
9.6%
1579
9.5%
ValueCountFrequency (%)
.3536
50.0%
/2652
37.5%
:884
 
12.5%
ValueCountFrequency (%)
_558
100.0%
ValueCountFrequency (%)
-586
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin56929
79.9%
Common14296
 
20.1%

Most frequent character per script

ValueCountFrequency (%)
t4108
 
7.2%
m3264
 
5.7%
d3236
 
5.7%
s2442
 
4.3%
e2436
 
4.3%
h2364
 
4.2%
i2346
 
4.1%
p2320
 
4.1%
b2174
 
3.8%
a1662
 
2.9%
Other values (42)30577
53.7%
ValueCountFrequency (%)
.3536
24.7%
/2652
18.6%
:884
 
6.2%
8649
 
4.5%
0643
 
4.5%
7631
 
4.4%
4603
 
4.2%
5601
 
4.2%
9601
 
4.2%
2596
 
4.2%
Other values (5)2900
20.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII71225
100.0%

Most frequent character per block

ValueCountFrequency (%)
t4108
 
5.8%
.3536
 
5.0%
m3264
 
4.6%
d3236
 
4.5%
/2652
 
3.7%
s2442
 
3.4%
e2436
 
3.4%
h2364
 
3.3%
i2346
 
3.3%
p2320
 
3.3%
Other values (57)42521
59.7%

edited
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size7.9 KiB

author_flair_css_class
Categorical

MISSING

Distinct1
Distinct (%)16.7%
Missing984
Missing (%)99.4%
Memory size7.7 KiB
Moderator

Length

Max length9
Median length3
Mean length3.036363636
Min length3

Characters and Unicode

Total characters3006
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rownan
2nd rownan
3rd rownan
4th rownan
5th rownan
ValueCountFrequency (%)
Moderator6
 
0.6%
(Missing)984
99.4%
2021-01-12T21:07:44.053591image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T21:07:44.115440image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
nan984
99.4%
moderator6
 
0.6%

Most occurring characters

ValueCountFrequency (%)
n1968
65.5%
a990
32.9%
o12
 
0.4%
r12
 
0.4%
M6
 
0.2%
d6
 
0.2%
e6
 
0.2%
t6
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3000
99.8%
Uppercase Letter6
 
0.2%

Most frequent character per category

ValueCountFrequency (%)
n1968
65.6%
a990
33.0%
o12
 
0.4%
r12
 
0.4%
d6
 
0.2%
e6
 
0.2%
t6
 
0.2%
ValueCountFrequency (%)
M6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3006
100.0%

Most frequent character per script

ValueCountFrequency (%)
n1968
65.5%
a990
32.9%
o12
 
0.4%
r12
 
0.4%
M6
 
0.2%
d6
 
0.2%
e6
 
0.2%
t6
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII3006
100.0%

Most frequent character per block

ValueCountFrequency (%)
n1968
65.5%
a990
32.9%
o12
 
0.4%
r12
 
0.4%
M6
 
0.2%
d6
 
0.2%
e6
 
0.2%
t6
 
0.2%

author_flair_richtext
Unsupported

REJECTED
UNSUPPORTED

Missing4
Missing (%)0.4%
Memory size7.9 KiB

gildings
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size7.9 KiB

post_hint
Categorical

MISSING

Distinct5
Distinct (%)0.6%
Missing97
Missing (%)9.8%
Memory size7.7 KiB
image
436 
link
384 
rich:video
67 
hosted:video
 
3
self
 
3

Length

Max length12
Median length5
Mean length4.772727273
Min length3

Characters and Unicode

Total characters4725
Distinct characters18
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowlink
2nd rowimage
3rd rowimage
4th rowimage
5th rowimage
ValueCountFrequency (%)
image436
44.0%
link384
38.8%
rich:video67
 
6.8%
hosted:video3
 
0.3%
self3
 
0.3%
(Missing)97
 
9.8%
2021-01-12T21:07:44.264027image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T21:07:44.324865image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
image436
44.0%
link384
38.8%
nan97
 
9.8%
rich:video67
 
6.8%
hosted:video3
 
0.3%
self3
 
0.3%

Most occurring characters

ValueCountFrequency (%)
i957
20.3%
n578
12.2%
a533
11.3%
e512
10.8%
m436
9.2%
g436
9.2%
l387
8.2%
k384
8.1%
d73
 
1.5%
o73
 
1.5%
Other values (8)356
 
7.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4655
98.5%
Other Punctuation70
 
1.5%

Most frequent character per category

ValueCountFrequency (%)
i957
20.6%
n578
12.4%
a533
11.5%
e512
11.0%
m436
9.4%
g436
9.4%
l387
8.3%
k384
8.2%
d73
 
1.6%
o73
 
1.6%
Other values (7)286
 
6.1%
ValueCountFrequency (%)
:70
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin4655
98.5%
Common70
 
1.5%

Most frequent character per script

ValueCountFrequency (%)
i957
20.6%
n578
12.4%
a533
11.5%
e512
11.0%
m436
9.4%
g436
9.4%
l387
8.3%
k384
8.2%
d73
 
1.6%
o73
 
1.6%
Other values (7)286
 
6.1%
ValueCountFrequency (%)
:70
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII4725
100.0%

Most frequent character per block

ValueCountFrequency (%)
i957
20.3%
n578
12.2%
a533
11.3%
e512
10.8%
m436
9.2%
g436
9.2%
l387
8.2%
k384
8.1%
d73
 
1.5%
o73
 
1.5%
Other values (8)356
 
7.5%

content_categories
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing990
Missing (%)100.0%
Memory size7.9 KiB

is_self
Boolean

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size990.0 B
False
920 
True
 
70
ValueCountFrequency (%)
False920
92.9%
True70
 
7.1%
2021-01-12T21:07:44.395676image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

mod_note
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing990
Missing (%)100.0%
Memory size7.9 KiB

crosspost_parent_list
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing977
Missing (%)98.7%
Memory size7.9 KiB

created
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct990
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1610118243
Minimum1609714444
Maximum1610462189
Zeros0
Zeros (%)0.0%
Memory size7.7 KiB
2021-01-12T21:07:44.470476image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1609714444
5-th percentile1609843988
Q11609993329
median1610088143
Q31610251865
95-th percentile1610430603
Maximum1610462189
Range747745
Interquartile range (IQR)258535.75

Descriptive statistics

Standard deviation173770.9156
Coefficient of variation (CV)0.0001079243195
Kurtosis-0.8019262211
Mean1610118243
Median Absolute Deviation (MAD)108261.5
Skewness0.2728621604
Sum1.59401706 × 1012
Variance3.019633112 × 1010
MonotocityNot monotonic
2021-01-12T21:07:44.589156image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16103393441
 
0.1%
16103586311
 
0.1%
16103732341
 
0.1%
16100242111
 
0.1%
16101742581
 
0.1%
16100012941
 
0.1%
16103715571
 
0.1%
16099508321
 
0.1%
16101458291
 
0.1%
16100105701
 
0.1%
Other values (980)980
99.0%
ValueCountFrequency (%)
16097144441
0.1%
16097362331
0.1%
16097529581
0.1%
16097542651
0.1%
16097632141
0.1%
ValueCountFrequency (%)
16104621891
0.1%
16104609791
0.1%
16104608211
0.1%
16104605431
0.1%
16104598441
0.1%

link_flair_type
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
richtext
541 
text
449 

Length

Max length8
Median length8
Mean length6.185858586
Min length4

Characters and Unicode

Total characters6124
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowrichtext
2nd rowtext
3rd rowtext
4th rowrichtext
5th rowrichtext
ValueCountFrequency (%)
richtext541
54.6%
text449
45.4%
2021-01-12T21:07:44.802587image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T21:07:44.871403image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
richtext541
54.6%
text449
45.4%

Most occurring characters

ValueCountFrequency (%)
t1980
32.3%
e990
16.2%
x990
16.2%
r541
 
8.8%
i541
 
8.8%
c541
 
8.8%
h541
 
8.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6124
100.0%

Most frequent character per category

ValueCountFrequency (%)
t1980
32.3%
e990
16.2%
x990
16.2%
r541
 
8.8%
i541
 
8.8%
c541
 
8.8%
h541
 
8.8%

Most occurring scripts

ValueCountFrequency (%)
Latin6124
100.0%

Most frequent character per script

ValueCountFrequency (%)
t1980
32.3%
e990
16.2%
x990
16.2%
r541
 
8.8%
i541
 
8.8%
c541
 
8.8%
h541
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII6124
100.0%

Most frequent character per block

ValueCountFrequency (%)
t1980
32.3%
e990
16.2%
x990
16.2%
r541
 
8.8%
i541
 
8.8%
c541
 
8.8%
h541
 
8.8%

wls
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
6
980 
3
 
10

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters990
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row6
2nd row6
3rd row6
4th row6
5th row6
ValueCountFrequency (%)
6980
99.0%
310
 
1.0%
2021-01-12T21:07:45.023995image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T21:07:45.080845image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
6980
99.0%
310
 
1.0%

Most occurring characters

ValueCountFrequency (%)
6980
99.0%
310
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number990
100.0%

Most frequent character per category

ValueCountFrequency (%)
6980
99.0%
310
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Common990
100.0%

Most frequent character per script

ValueCountFrequency (%)
6980
99.0%
310
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII990
100.0%

Most frequent character per block

ValueCountFrequency (%)
6980
99.0%
310
 
1.0%

removed_by_category
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing990
Missing (%)100.0%
Memory size7.9 KiB

banned_by
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing990
Missing (%)100.0%
Memory size7.9 KiB
Distinct2
Distinct (%)0.2%
Missing4
Missing (%)0.4%
Memory size7.7 KiB
text
980 
richtext
 
6

Length

Max length8
Median length4
Mean length4.02020202
Min length3

Characters and Unicode

Total characters3980
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowtext
2nd rowtext
3rd rowtext
4th rowtext
5th rowtext
ValueCountFrequency (%)
text980
99.0%
richtext6
 
0.6%
(Missing)4
 
0.4%
2021-01-12T21:07:45.235429image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T21:07:45.294272image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
text980
99.0%
richtext6
 
0.6%
nan4
 
0.4%

Most occurring characters

ValueCountFrequency (%)
t1972
49.5%
e986
24.8%
x986
24.8%
n8
 
0.2%
r6
 
0.2%
i6
 
0.2%
c6
 
0.2%
h6
 
0.2%
a4
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3980
100.0%

Most frequent character per category

ValueCountFrequency (%)
t1972
49.5%
e986
24.8%
x986
24.8%
n8
 
0.2%
r6
 
0.2%
i6
 
0.2%
c6
 
0.2%
h6
 
0.2%
a4
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin3980
100.0%

Most frequent character per script

ValueCountFrequency (%)
t1972
49.5%
e986
24.8%
x986
24.8%
n8
 
0.2%
r6
 
0.2%
i6
 
0.2%
c6
 
0.2%
h6
 
0.2%
a4
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII3980
100.0%

Most frequent character per block

ValueCountFrequency (%)
t1972
49.5%
e986
24.8%
x986
24.8%
n8
 
0.2%
r6
 
0.2%
i6
 
0.2%
c6
 
0.2%
h6
 
0.2%
a4
 
0.1%

domain
Categorical

HIGH CARDINALITY

Distinct148
Distinct (%)14.9%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
i.redd.it
420 
self.democrats
70 
youtu.be
47 
twitter.com
 
37
cnn.com
 
26
Other values (143)
390 

Length

Max length43
Median length9
Mean length10.8
Min length6

Characters and Unicode

Total characters10692
Distinct characters36
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique90 ?
Unique (%)9.1%

Sample

1st rowself.JoeBiden
2nd rowi.redd.it
3rd rowi.redd.it
4th rowi.redd.it
5th rowi.redd.it
ValueCountFrequency (%)
i.redd.it420
42.4%
self.democrats70
 
7.1%
youtu.be47
 
4.7%
twitter.com37
 
3.7%
cnn.com26
 
2.6%
thehill.com22
 
2.2%
youtube.com19
 
1.9%
nbcnews.com15
 
1.5%
i.imgur.com14
 
1.4%
apnews.com14
 
1.4%
Other values (138)306
30.9%
2021-01-12T21:07:45.498791image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
i.redd.it420
42.4%
self.democrats70
 
7.1%
youtu.be47
 
4.7%
twitter.com37
 
3.7%
cnn.com26
 
2.6%
thehill.com22
 
2.2%
youtube.com19
 
1.9%
nbcnews.com15
 
1.5%
apnews.com14
 
1.4%
i.imgur.com14
 
1.4%
Other values (138)306
30.9%

Most occurring characters

ValueCountFrequency (%)
.1489
13.9%
i1154
10.8%
d1018
9.5%
e1013
9.5%
t932
8.7%
o777
 
7.3%
r680
 
6.4%
c626
 
5.9%
m582
 
5.4%
s388
 
3.6%
Other values (26)2033
19.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter9183
85.9%
Other Punctuation1489
 
13.9%
Decimal Number12
 
0.1%
Uppercase Letter6
 
0.1%
Dash Punctuation2
 
< 0.1%

Most frequent character per category

ValueCountFrequency (%)
i1154
12.6%
d1018
11.1%
e1013
11.0%
t932
10.1%
o777
8.5%
r680
7.4%
c626
 
6.8%
m582
 
6.3%
s388
 
4.2%
n325
 
3.5%
Other values (16)1688
18.4%
ValueCountFrequency (%)
13
25.0%
23
25.0%
42
16.7%
32
16.7%
71
 
8.3%
91
 
8.3%
ValueCountFrequency (%)
J3
50.0%
B3
50.0%
ValueCountFrequency (%)
.1489
100.0%
ValueCountFrequency (%)
-2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin9189
85.9%
Common1503
 
14.1%

Most frequent character per script

ValueCountFrequency (%)
i1154
12.6%
d1018
11.1%
e1013
11.0%
t932
10.1%
o777
8.5%
r680
7.4%
c626
 
6.8%
m582
 
6.3%
s388
 
4.2%
n325
 
3.5%
Other values (18)1694
18.4%
ValueCountFrequency (%)
.1489
99.1%
13
 
0.2%
23
 
0.2%
42
 
0.1%
32
 
0.1%
-2
 
0.1%
71
 
0.1%
91
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII10692
100.0%

Most frequent character per block

ValueCountFrequency (%)
.1489
13.9%
i1154
10.8%
d1018
9.5%
e1013
9.5%
t932
8.7%
o777
 
7.3%
r680
 
6.4%
c626
 
5.9%
m582
 
5.4%
s388
 
3.6%
Other values (26)2033
19.0%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size990.0 B
False
877 
True
113 
ValueCountFrequency (%)
False877
88.6%
True113
 
11.4%
2021-01-12T21:07:45.569601image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

selftext_html
Categorical

HIGH CARDINALITY
MISSING
UNIFORM

Distinct57
Distinct (%)100.0%
Missing933
Missing (%)94.2%
Memory size7.7 KiB
&lt;!-- SC_OFF --&gt;&lt;div class="md"&gt;&lt;p&gt;Remember the actions taken&lt;/p&gt; &lt;p&gt;Remember the reactions&lt;/p&gt; &lt;p&gt;Remember who offered support&lt;/p&gt; &lt;p&gt;Remember who condemned chaos&lt;/p&gt; &lt;p&gt;Remember who was silent&lt;/p&gt; &lt;p&gt;Remember who was loud&lt;/p&gt; &lt;p&gt;Remember who was violent and chaotic&lt;/p&gt; &lt;p&gt;Remember who was peaceful and resilient&lt;/p&gt; &lt;/div&gt;&lt;!-- SC_ON --&gt;
 
1
&lt;!-- SC_OFF --&gt;&lt;div class="md"&gt;&lt;p&gt;I was born in Havana, Cuba. Came to the US in the ‘80s, became old enough to vote in 1997 and voted for the first time in 2000. I voted for Bush twice, McCain, Romney, and Trump in 2016. Thanks to Trump’s reckless administration, I learned I was being used so I left the Republican Party in 2017. I became a Democrat in 2019, and voted Democratic for the first time of my life, and that Democrat was Joe Biden for POTUS.&lt;/p&gt; &lt;/div&gt;&lt;!-- SC_ON --&gt;
 
1
&lt;!-- SC_OFF --&gt;&lt;div class="md"&gt;&lt;p&gt;and that’s universal healthcare, a living wage, universal childcare, more access to higher education, and a progressive tax rate. Because that’s what you fucking deserve.&lt;/p&gt; &lt;/div&gt;&lt;!-- SC_ON --&gt;
 
1
&lt;!-- SC_OFF --&gt;&lt;div class="md"&gt;&lt;p&gt;Don&amp;#39;t think the idea lesson protesters are white Republicans and that we need to let up on this position now&lt;/p&gt; &lt;/div&gt;&lt;!-- SC_ON --&gt;
 
1
&lt;!-- SC_OFF --&gt;&lt;div class="md"&gt;&lt;p&gt;I may live in the deathscape known as West Virginia, but I just wanted to say that I believe in you, Georgia. We can do this! Let’s get these two wins and get rid of the Turtle!&lt;/p&gt; &lt;/div&gt;&lt;!-- SC_ON --&gt;
 
1
Other values (52)
52 

Length

Max length7487
Median length3
Mean length36.75353535
Min length3

Characters and Unicode

Total characters36386
Distinct characters89
Distinct categories15 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)100.0%

Sample

1st rownan
2nd rownan
3rd rownan
4th rownan
5th rownan
ValueCountFrequency (%)
&lt;!-- SC_OFF --&gt;&lt;div class="md"&gt;&lt;p&gt;Remember the actions taken&lt;/p&gt; &lt;p&gt;Remember the reactions&lt;/p&gt; &lt;p&gt;Remember who offered support&lt;/p&gt; &lt;p&gt;Remember who condemned chaos&lt;/p&gt; &lt;p&gt;Remember who was silent&lt;/p&gt; &lt;p&gt;Remember who was loud&lt;/p&gt; &lt;p&gt;Remember who was violent and chaotic&lt;/p&gt; &lt;p&gt;Remember who was peaceful and resilient&lt;/p&gt; &lt;/div&gt;&lt;!-- SC_ON --&gt;1
 
0.1%
&lt;!-- SC_OFF --&gt;&lt;div class="md"&gt;&lt;p&gt;I was born in Havana, Cuba. Came to the US in the ‘80s, became old enough to vote in 1997 and voted for the first time in 2000. I voted for Bush twice, McCain, Romney, and Trump in 2016. Thanks to Trump’s reckless administration, I learned I was being used so I left the Republican Party in 2017. I became a Democrat in 2019, and voted Democratic for the first time of my life, and that Democrat was Joe Biden for POTUS.&lt;/p&gt; &lt;/div&gt;&lt;!-- SC_ON --&gt;1
 
0.1%
&lt;!-- SC_OFF --&gt;&lt;div class="md"&gt;&lt;p&gt;and that’s universal healthcare, a living wage, universal childcare, more access to higher education, and a progressive tax rate. Because that’s what you fucking deserve.&lt;/p&gt; &lt;/div&gt;&lt;!-- SC_ON --&gt;1
 
0.1%
&lt;!-- SC_OFF --&gt;&lt;div class="md"&gt;&lt;p&gt;Don&amp;#39;t think the idea lesson protesters are white Republicans and that we need to let up on this position now&lt;/p&gt; &lt;/div&gt;&lt;!-- SC_ON --&gt;1
 
0.1%
&lt;!-- SC_OFF --&gt;&lt;div class="md"&gt;&lt;p&gt;I may live in the deathscape known as West Virginia, but I just wanted to say that I believe in you, Georgia. We can do this! Let’s get these two wins and get rid of the Turtle!&lt;/p&gt; &lt;/div&gt;&lt;!-- SC_ON --&gt;1
 
0.1%
&lt;!-- SC_OFF --&gt;&lt;div class="md"&gt;&lt;p&gt;It&amp;#39;s been a long run. Thank you Stacey Abrams about both of Georgia&amp;#39;s new, blue Senators for pushing it this far. The last 4 years were hard and November was agonizing. This feels like it could be a positive turn that I&amp;#39;m ready to believe in.&lt;/p&gt; &lt;/div&gt;&lt;!-- SC_ON --&gt;1
 
0.1%
&lt;!-- SC_OFF --&gt;&lt;div class="md"&gt;&lt;p&gt;Senators Raphael Warnock and Jon Ossoff&lt;/p&gt; &lt;p&gt;Minority Leader Mitch McConnell&lt;/p&gt; &lt;/div&gt;&lt;!-- SC_ON --&gt;1
 
0.1%
&lt;!-- SC_OFF --&gt;&lt;div class="md"&gt;&lt;p&gt;I&amp;#39;m just beside myself trying to understand how the vote tally&amp;#39;s aren&amp;#39;t exactly the same. &lt;/p&gt; &lt;p&gt;Or is this an instance of people proactively voting for a specific person (Warnock), over just voting party lines.&lt;/p&gt; &lt;/div&gt;&lt;!-- SC_ON --&gt;1
 
0.1%
&lt;!-- SC_OFF --&gt;&lt;div class="md"&gt;&lt;p&gt;Your responsible: &lt;/p&gt; &lt;p&gt;Marsha Blackburn of Tennessee Mike Braun of Indiana Ted Cruz of Texas Steve Daines of Montana Bill Hagerty of Tennessee Josh Hawley of Missouri Ron Johnson of Wisconsin John Kennedy of Louisiana James Lankford of Oklahoma Cynthia Lummis of Wyoming Roger Marshall of Kansas Rick Scott of Florida Tommy Tuberville of Alabama Kelly Loeffler of Georgia&lt;/p&gt; &lt;/div&gt;&lt;!-- SC_ON --&gt;1
 
0.1%
&lt;!-- SC_OFF --&gt;&lt;div class="md"&gt;&lt;p&gt;With the Democratic Party having majority of the House, the Senate and the Presidency, I figured now would be a good time to gauge how at least the next 4 years will go and how the people think it should go in regards to gun control.&lt;/p&gt; &lt;/div&gt;&lt;!-- SC_ON --&gt;1
 
0.1%
Other values (47)47
 
4.7%
(Missing)933
94.2%
2021-01-12T21:07:45.779042image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan933
 
16.3%
the225
 
3.9%
to127
 
2.2%
of104
 
1.8%
a101
 
1.8%
and100
 
1.7%
in76
 
1.3%
i70
 
1.2%
that59
 
1.0%
sc_on57
 
1.0%
Other values (1546)3880
67.7%

Most occurring characters

ValueCountFrequency (%)
4625
 
12.7%
n3241
 
8.9%
t2854
 
7.8%
a2659
 
7.3%
e2463
 
6.8%
o1560
 
4.3%
i1478
 
4.1%
l1368
 
3.8%
s1305
 
3.6%
;1220
 
3.4%
Other values (79)13613
37.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter25758
70.8%
Space Separator4625
 
12.7%
Other Punctuation3403
 
9.4%
Uppercase Letter1304
 
3.6%
Dash Punctuation491
 
1.3%
Decimal Number393
 
1.1%
Control187
 
0.5%
Connector Punctuation114
 
0.3%
Math Symbol68
 
0.2%
Final Punctuation19
 
0.1%
Other values (5)24
 
0.1%

Most frequent character per category

ValueCountFrequency (%)
n3241
12.6%
t2854
11.1%
a2659
 
10.3%
e2463
 
9.6%
o1560
 
6.1%
i1478
 
5.7%
l1368
 
5.3%
s1305
 
5.1%
r1142
 
4.4%
h1014
 
3.9%
Other values (16)6674
25.9%
ValueCountFrequency (%)
S155
11.9%
C152
11.7%
I145
11.1%
O137
10.5%
F128
9.8%
T81
 
6.2%
N77
 
5.9%
A62
 
4.8%
R56
 
4.3%
W42
 
3.2%
Other values (15)269
20.6%
ValueCountFrequency (%)
;1220
35.9%
&1100
32.3%
.266
 
7.8%
/244
 
7.2%
,178
 
5.2%
"128
 
3.8%
!123
 
3.6%
#87
 
2.6%
?29
 
0.9%
:19
 
0.6%
Other values (4)9
 
0.3%
ValueCountFrequency (%)
3100
25.4%
997
24.7%
253
13.5%
044
11.2%
137
 
9.4%
517
 
4.3%
815
 
3.8%
613
 
3.3%
711
 
2.8%
46
 
1.5%
ValueCountFrequency (%)
-490
99.8%
1
 
0.2%
ValueCountFrequency (%)
18
94.7%
1
 
5.3%
ValueCountFrequency (%)
1
50.0%
1
50.0%
ValueCountFrequency (%)
4625
100.0%
ValueCountFrequency (%)
_114
100.0%
ValueCountFrequency (%)
=68
100.0%
ValueCountFrequency (%)
187
100.0%
ValueCountFrequency (%)
(9
100.0%
ValueCountFrequency (%)
)9
100.0%
ValueCountFrequency (%)
$3
100.0%
ValueCountFrequency (%)
🌊1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin27062
74.4%
Common9324
 
25.6%

Most frequent character per script

ValueCountFrequency (%)
n3241
12.0%
t2854
 
10.5%
a2659
 
9.8%
e2463
 
9.1%
o1560
 
5.8%
i1478
 
5.5%
l1368
 
5.1%
s1305
 
4.8%
r1142
 
4.2%
h1014
 
3.7%
Other values (41)7978
29.5%
ValueCountFrequency (%)
4625
49.6%
;1220
 
13.1%
&1100
 
11.8%
-490
 
5.3%
.266
 
2.9%
/244
 
2.6%
187
 
2.0%
,178
 
1.9%
"128
 
1.4%
!123
 
1.3%
Other values (28)763
 
8.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII36358
99.9%
Punctuation23
 
0.1%
None5
 
< 0.1%

Most frequent character per block

ValueCountFrequency (%)
4625
 
12.7%
n3241
 
8.9%
t2854
 
7.8%
a2659
 
7.3%
e2463
 
6.8%
o1560
 
4.3%
i1478
 
4.1%
l1368
 
3.8%
s1305
 
3.6%
;1220
 
3.4%
Other values (71)13585
37.4%
ValueCountFrequency (%)
18
78.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
ValueCountFrequency (%)
§4
80.0%
🌊1
 
20.0%

likes
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing990
Missing (%)100.0%
Memory size7.9 KiB

suggested_sort
Categorical

MISSING

Distinct2
Distinct (%)50.0%
Missing986
Missing (%)99.6%
Memory size7.7 KiB
new
confidence

Length

Max length10
Median length3
Mean length3.007070707
Min length3

Characters and Unicode

Total characters2977
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)25.0%

Sample

1st rownew
2nd rownan
3rd rownan
4th rownan
5th rownan
ValueCountFrequency (%)
new3
 
0.3%
confidence1
 
0.1%
(Missing)986
99.6%
2021-01-12T21:07:45.995461image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T21:07:46.058297image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
nan986
99.6%
new3
 
0.3%
confidence1
 
0.1%

Most occurring characters

ValueCountFrequency (%)
n1977
66.4%
a986
33.1%
e5
 
0.2%
w3
 
0.1%
c2
 
0.1%
o1
 
< 0.1%
f1
 
< 0.1%
i1
 
< 0.1%
d1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2977
100.0%

Most frequent character per category

ValueCountFrequency (%)
n1977
66.4%
a986
33.1%
e5
 
0.2%
w3
 
0.1%
c2
 
0.1%
o1
 
< 0.1%
f1
 
< 0.1%
i1
 
< 0.1%
d1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin2977
100.0%

Most frequent character per script

ValueCountFrequency (%)
n1977
66.4%
a986
33.1%
e5
 
0.2%
w3
 
0.1%
c2
 
0.1%
o1
 
< 0.1%
f1
 
< 0.1%
i1
 
< 0.1%
d1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII2977
100.0%

Most frequent character per block

ValueCountFrequency (%)
n1977
66.4%
a986
33.1%
e5
 
0.2%
w3
 
0.1%
c2
 
0.1%
o1
 
< 0.1%
f1
 
< 0.1%
i1
 
< 0.1%
d1
 
< 0.1%

banned_at_utc
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing990
Missing (%)100.0%
Memory size7.9 KiB

url_overridden_by_dest
Categorical

HIGH CARDINALITY
MISSING
UNIFORM

Distinct916
Distinct (%)99.6%
Missing70
Missing (%)7.1%
Memory size7.7 KiB
https://www.theatlantic.com/ideas/archive/2021/01/remove-trump-tonight/617576/
 
2
https://www.bbc.co.uk/news/technology-55569604
 
2
https://www.nytimes.com/interactive/2021/01/07/us/elections/electoral-college-biden-objectors.html
 
2
https://www.cnn.com/2021/01/07/politics/trump-biden-us-capitol-electoral-college-insurrection/index.html
 
2
https://www.politico.com/news/2021/01/06/biden-to-tap-merrick-garland-for-attorney-general-455410
 
1
Other values (911)
911 

Length

Max length341
Median length35
Mean length58.3020202
Min length3

Characters and Unicode

Total characters57719
Distinct characters73
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique912 ?
Unique (%)99.1%

Sample

1st row/r/JoeBiden/comments/kv4jen/house_democrats_launch_second_impeachment_of/
2nd rowhttps://i.redd.it/sq8b597wpsa61.jpg
3rd rowhttps://i.redd.it/ewmxi3oh0qa61.jpg
4th rowhttps://i.redd.it/863qmtjcbsa61.jpg
5th rowhttps://i.redd.it/nil93j0cmsa61.jpg
ValueCountFrequency (%)
https://www.theatlantic.com/ideas/archive/2021/01/remove-trump-tonight/617576/2
 
0.2%
https://www.bbc.co.uk/news/technology-555696042
 
0.2%
https://www.nytimes.com/interactive/2021/01/07/us/elections/electoral-college-biden-objectors.html2
 
0.2%
https://www.cnn.com/2021/01/07/politics/trump-biden-us-capitol-electoral-college-insurrection/index.html2
 
0.2%
https://www.politico.com/news/2021/01/06/biden-to-tap-merrick-garland-for-attorney-general-4554101
 
0.1%
https://www.fbi.gov/contact-us/field-offices/washingtondc/news/fbi-seeking-information-related-to-violent-activity-at-the-us-capitol-building1
 
0.1%
https://i.redd.it/bc2c328z9t961.jpg1
 
0.1%
https://i.redd.it/atjmajk1ld961.jpg1
 
0.1%
https://apnews.com/article/joe-biden-politics-lisa-monaco-merrick-garland-courts-e7972db4cd96352d028af3167b2534811
 
0.1%
https://i.redd.it/wn7v2yav5ca61.jpg1
 
0.1%
Other values (906)906
91.5%
(Missing)70
 
7.1%
2021-01-12T21:07:46.270727image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan70
 
7.1%
https://www.cnn.com/2021/01/07/politics/trump-biden-us-capitol-electoral-college-insurrection/index.html2
 
0.2%
https://www.theatlantic.com/ideas/archive/2021/01/remove-trump-tonight/6175762
 
0.2%
https://www.nytimes.com/interactive/2021/01/07/us/elections/electoral-college-biden-objectors.html2
 
0.2%
https://www.bbc.co.uk/news/technology-555696042
 
0.2%
https://twitter.com/realdonaldtrump/status/1287877621380837378?ref_src=twsrc%5etfw%7ctwcamp%5etweetembed%7ctwterm%5e1287877621380837378%7ctwgr%5e%7ctwcon%5es1_&amp;ref_url=https%3a%2f%2fwww.cbs17.com%2fnews%2fnational-news%2ftrump-tweet-threatening-prison-time-for-those-who-protest-at-federal-buildings-resurfaces-amid-capitol-hill-chaos%2f1
 
0.1%
https://i.redd.it/c3hrmczb32a61.jpg1
 
0.1%
https://i.redd.it/webvfod2bx961.png1
 
0.1%
https://www.fbi.gov/contact-us/field-offices/washingtondc/news/fbi-seeking-information-related-to-violent-activity-at-the-us-capitol-building1
 
0.1%
https://i.redd.it/b1i1utxswfa61.jpg1
 
0.1%
Other values (907)907
91.6%

Most occurring characters

ValueCountFrequency (%)
t4710
 
8.2%
/3836
 
6.6%
e3257
 
5.6%
i2946
 
5.1%
s2902
 
5.0%
-2681
 
4.6%
o2430
 
4.2%
p2391
 
4.1%
a2322
 
4.0%
.2245
 
3.9%
Other values (63)27999
48.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter40690
70.5%
Other Punctuation7158
 
12.4%
Decimal Number6303
 
10.9%
Dash Punctuation2681
 
4.6%
Uppercase Letter668
 
1.2%
Connector Punctuation121
 
0.2%
Math Symbol98
 
0.2%

Most frequent character per category

ValueCountFrequency (%)
t4710
 
11.6%
e3257
 
8.0%
i2946
 
7.2%
s2902
 
7.1%
o2430
 
6.0%
p2391
 
5.9%
a2322
 
5.7%
r2228
 
5.5%
n2072
 
5.1%
d1809
 
4.4%
Other values (16)13623
33.5%
ValueCountFrequency (%)
S43
 
6.4%
C42
 
6.3%
B40
 
6.0%
U35
 
5.2%
P32
 
4.8%
R32
 
4.8%
F32
 
4.8%
I31
 
4.6%
T29
 
4.3%
H28
 
4.2%
Other values (16)324
48.5%
ValueCountFrequency (%)
11252
19.9%
6870
13.8%
0778
12.3%
2727
11.5%
9587
9.3%
5483
 
7.7%
3431
 
6.8%
4410
 
6.5%
7388
 
6.2%
8377
 
6.0%
ValueCountFrequency (%)
/3836
53.6%
.2245
31.4%
:917
 
12.8%
?73
 
1.0%
%32
 
0.4%
&26
 
0.4%
;26
 
0.4%
#3
 
< 0.1%
ValueCountFrequency (%)
_121
100.0%
ValueCountFrequency (%)
-2681
100.0%
ValueCountFrequency (%)
=98
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin41358
71.7%
Common16361
 
28.3%

Most frequent character per script

ValueCountFrequency (%)
t4710
 
11.4%
e3257
 
7.9%
i2946
 
7.1%
s2902
 
7.0%
o2430
 
5.9%
p2391
 
5.8%
a2322
 
5.6%
r2228
 
5.4%
n2072
 
5.0%
d1809
 
4.4%
Other values (42)14291
34.6%
ValueCountFrequency (%)
/3836
23.4%
-2681
16.4%
.2245
13.7%
11252
 
7.7%
:917
 
5.6%
6870
 
5.3%
0778
 
4.8%
2727
 
4.4%
9587
 
3.6%
5483
 
3.0%
Other values (11)1985
12.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII57719
100.0%

Most frequent character per block

ValueCountFrequency (%)
t4710
 
8.2%
/3836
 
6.6%
e3257
 
5.6%
i2946
 
5.1%
s2902
 
5.0%
-2681
 
4.6%
o2430
 
4.2%
p2391
 
4.1%
a2322
 
4.0%
.2245
 
3.9%
Other values (63)27999
48.5%

view_count
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing990
Missing (%)100.0%
Memory size7.9 KiB

archived
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size990.0 B
False
990 
ValueCountFrequency (%)
False990
100.0%
2021-01-12T21:07:46.349514image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

no_follow
Boolean

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size990.0 B
False
953 
True
 
37
ValueCountFrequency (%)
False953
96.3%
True37
 
3.7%
2021-01-12T21:07:46.377442image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

is_crosspostable
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size990.0 B
False
990 
ValueCountFrequency (%)
False990
100.0%
2021-01-12T21:07:46.414341image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

pinned
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size990.0 B
False
990 
ValueCountFrequency (%)
False990
100.0%
2021-01-12T21:07:46.441271image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

over_18
Boolean

HIGH CORRELATION

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size990.0 B
False
980 
True
 
10
ValueCountFrequency (%)
False980
99.0%
True10
 
1.0%
2021-01-12T21:07:46.469194image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

preview
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing97
Missing (%)9.8%
Memory size7.9 KiB

all_awardings
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size7.9 KiB

awarders
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size7.9 KiB

media_only
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size990.0 B
False
990 
ValueCountFrequency (%)
False990
100.0%
2021-01-12T21:07:46.507093image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

link_flair_template_id
Categorical

MISSING

Distinct23
Distinct (%)4.8%
Missing510
Missing (%)51.5%
Memory size7.7 KiB
ec699eba-dd59-11ea-8dc8-0ecbe56cff1d
94 
d5bbc84c-dd58-11ea-b388-0e8e81330acb
79 
fc8afa6e-dd59-11ea-8541-0e09e4b7c31f
70 
ef599158-2dbc-11eb-a4b2-0e1a5aebf877
46 
e16437a2-dd57-11ea-a85d-0e32d293b691
43 
Other values (18)
148 

Length

Max length36
Median length3
Mean length19
Min length3

Characters and Unicode

Total characters18810
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)0.8%

Sample

1st row67d78188-5420-11eb-8a07-0e0fd072bff5
2nd rownan
3rd rownan
4th row1a2d922c-dd58-11ea-812c-0e3b77e24cb9
5th rowd5bbc84c-dd58-11ea-b388-0e8e81330acb
ValueCountFrequency (%)
ec699eba-dd59-11ea-8dc8-0ecbe56cff1d94
 
9.5%
d5bbc84c-dd58-11ea-b388-0e8e81330acb79
 
8.0%
fc8afa6e-dd59-11ea-8541-0e09e4b7c31f70
 
7.1%
ef599158-2dbc-11eb-a4b2-0e1a5aebf87746
 
4.6%
e16437a2-dd57-11ea-a85d-0e32d293b69143
 
4.3%
0bf3b48c-dd5a-11ea-891c-0eb295b8865f37
 
3.7%
fe9e95e2-dd57-11ea-bfc9-0e97de11b9ef26
 
2.6%
2fd2a1b2-dd58-11ea-be1a-0e61f7f81e3317
 
1.7%
366aed66-dd5a-11ea-84d2-0e5d79fe92b313
 
1.3%
46d6e85a-dd58-11ea-a039-0e4e897c1c3111
 
1.1%
Other values (13)44
 
4.4%
(Missing)510
51.5%
2021-01-12T21:07:46.662677image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan510
51.5%
ec699eba-dd59-11ea-8dc8-0ecbe56cff1d94
 
9.5%
d5bbc84c-dd58-11ea-b388-0e8e81330acb79
 
8.0%
fc8afa6e-dd59-11ea-8541-0e09e4b7c31f70
 
7.1%
ef599158-2dbc-11eb-a4b2-0e1a5aebf87746
 
4.6%
e16437a2-dd57-11ea-a85d-0e32d293b69143
 
4.3%
0bf3b48c-dd5a-11ea-891c-0eb295b8865f37
 
3.7%
fe9e95e2-dd57-11ea-bfc9-0e97de11b9ef26
 
2.6%
2fd2a1b2-dd58-11ea-be1a-0e61f7f81e3317
 
1.7%
366aed66-dd5a-11ea-84d2-0e5d79fe92b313
 
1.3%
Other values (14)55
 
5.6%

Most occurring characters

ValueCountFrequency (%)
-1920
 
10.2%
e1857
 
9.9%
11715
 
9.1%
a1638
 
8.7%
d1389
 
7.4%
81283
 
6.8%
b1099
 
5.8%
51035
 
5.5%
n1020
 
5.4%
c1016
 
5.4%
Other values (8)4838
25.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter8756
46.5%
Decimal Number8134
43.2%
Dash Punctuation1920
 
10.2%

Most frequent character per category

ValueCountFrequency (%)
11715
21.1%
81283
15.8%
51035
12.7%
9930
11.4%
0714
8.8%
3606
 
7.5%
6519
 
6.4%
2462
 
5.7%
4455
 
5.6%
7415
 
5.1%
ValueCountFrequency (%)
e1857
21.2%
a1638
18.7%
d1389
15.9%
b1099
12.6%
n1020
11.6%
c1016
11.6%
f737
 
8.4%
ValueCountFrequency (%)
-1920
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common10054
53.5%
Latin8756
46.5%

Most frequent character per script

ValueCountFrequency (%)
-1920
19.1%
11715
17.1%
81283
12.8%
51035
10.3%
9930
9.3%
0714
 
7.1%
3606
 
6.0%
6519
 
5.2%
2462
 
4.6%
4455
 
4.5%
ValueCountFrequency (%)
e1857
21.2%
a1638
18.7%
d1389
15.9%
b1099
12.6%
n1020
11.6%
c1016
11.6%
f737
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII18810
100.0%

Most frequent character per block

ValueCountFrequency (%)
-1920
 
10.2%
e1857
 
9.9%
11715
 
9.1%
a1638
 
8.7%
d1389
 
7.4%
81283
 
6.8%
b1099
 
5.8%
51035
 
5.5%
n1020
 
5.4%
c1016
 
5.4%
Other values (8)4838
25.7%

can_gild
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size990.0 B
False
990 
ValueCountFrequency (%)
False990
100.0%
2021-01-12T21:07:46.915999image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

spoiler
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size990.0 B
False
990 
ValueCountFrequency (%)
False990
100.0%
2021-01-12T21:07:46.943924image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

locked
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size990.0 B
False
990 
ValueCountFrequency (%)
False990
100.0%
2021-01-12T21:07:46.970850image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

author_flair_text
Categorical

MISSING

Distinct1
Distinct (%)16.7%
Missing984
Missing (%)99.4%
Memory size7.7 KiB
Moderator

Length

Max length9
Median length3
Mean length3.036363636
Min length3

Characters and Unicode

Total characters3006
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rownan
2nd rownan
3rd rownan
4th rownan
5th rownan
ValueCountFrequency (%)
Moderator6
 
0.6%
(Missing)984
99.4%
2021-01-12T21:07:47.118463image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T21:07:47.180292image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
nan984
99.4%
moderator6
 
0.6%

Most occurring characters

ValueCountFrequency (%)
n1968
65.5%
a990
32.9%
o12
 
0.4%
r12
 
0.4%
M6
 
0.2%
d6
 
0.2%
e6
 
0.2%
t6
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3000
99.8%
Uppercase Letter6
 
0.2%

Most frequent character per category

ValueCountFrequency (%)
n1968
65.6%
a990
33.0%
o12
 
0.4%
r12
 
0.4%
d6
 
0.2%
e6
 
0.2%
t6
 
0.2%
ValueCountFrequency (%)
M6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3006
100.0%

Most frequent character per script

ValueCountFrequency (%)
n1968
65.5%
a990
32.9%
o12
 
0.4%
r12
 
0.4%
M6
 
0.2%
d6
 
0.2%
e6
 
0.2%
t6
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII3006
100.0%

Most frequent character per block

ValueCountFrequency (%)
n1968
65.5%
a990
32.9%
o12
 
0.4%
r12
 
0.4%
M6
 
0.2%
d6
 
0.2%
e6
 
0.2%
t6
 
0.2%

treatment_tags
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size7.9 KiB

visited
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size990.0 B
False
990 
ValueCountFrequency (%)
False990
100.0%
2021-01-12T21:07:47.209215image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

removed_by
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing990
Missing (%)100.0%
Memory size7.9 KiB

num_reports
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing990
Missing (%)100.0%
Memory size7.9 KiB

distinguished
Categorical

MISSING

Distinct1
Distinct (%)50.0%
Missing988
Missing (%)99.8%
Memory size7.7 KiB
moderator

Length

Max length9
Median length3
Mean length3.012121212
Min length3

Characters and Unicode

Total characters2982
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rownan
2nd rownan
3rd rownan
4th rownan
5th rownan
ValueCountFrequency (%)
moderator2
 
0.2%
(Missing)988
99.8%
2021-01-12T21:07:47.354825image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T21:07:47.415662image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
nan988
99.8%
moderator2
 
0.2%

Most occurring characters

ValueCountFrequency (%)
n1976
66.3%
a990
33.2%
o4
 
0.1%
r4
 
0.1%
m2
 
0.1%
d2
 
0.1%
e2
 
0.1%
t2
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2982
100.0%

Most frequent character per category

ValueCountFrequency (%)
n1976
66.3%
a990
33.2%
o4
 
0.1%
r4
 
0.1%
m2
 
0.1%
d2
 
0.1%
e2
 
0.1%
t2
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin2982
100.0%

Most frequent character per script

ValueCountFrequency (%)
n1976
66.3%
a990
33.2%
o4
 
0.1%
r4
 
0.1%
m2
 
0.1%
d2
 
0.1%
e2
 
0.1%
t2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII2982
100.0%

Most frequent character per block

ValueCountFrequency (%)
n1976
66.3%
a990
33.2%
o4
 
0.1%
r4
 
0.1%
m2
 
0.1%
d2
 
0.1%
e2
 
0.1%
t2
 
0.1%

subreddit_id
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
t5_2qn70
990 

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters7920
Distinct characters8
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowt5_2qn70
2nd rowt5_2qn70
3rd rowt5_2qn70
4th rowt5_2qn70
5th rowt5_2qn70
ValueCountFrequency (%)
t5_2qn70990
100.0%
2021-01-12T21:07:47.555292image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T21:07:47.611140image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
t5_2qn70990
100.0%

Most occurring characters

ValueCountFrequency (%)
t990
12.5%
5990
12.5%
_990
12.5%
2990
12.5%
q990
12.5%
n990
12.5%
7990
12.5%
0990
12.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number3960
50.0%
Lowercase Letter2970
37.5%
Connector Punctuation990
 
12.5%

Most frequent character per category

ValueCountFrequency (%)
5990
25.0%
2990
25.0%
7990
25.0%
0990
25.0%
ValueCountFrequency (%)
t990
33.3%
q990
33.3%
n990
33.3%
ValueCountFrequency (%)
_990
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common4950
62.5%
Latin2970
37.5%

Most frequent character per script

ValueCountFrequency (%)
5990
20.0%
_990
20.0%
2990
20.0%
7990
20.0%
0990
20.0%
ValueCountFrequency (%)
t990
33.3%
q990
33.3%
n990
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII7920
100.0%

Most frequent character per block

ValueCountFrequency (%)
t990
12.5%
5990
12.5%
_990
12.5%
2990
12.5%
q990
12.5%
n990
12.5%
7990
12.5%
0990
12.5%

mod_reason_by
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing990
Missing (%)100.0%
Memory size7.9 KiB

removal_reason
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing990
Missing (%)100.0%
Memory size7.9 KiB
Distinct18
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
556 
#5f9dd2
94 
#ff0000
79 
#349e48
70 
#ff4500
 
45
Other values (13)
146 

Length

Max length7
Median length0
Mean length3.068686869
Min length0

Characters and Unicode

Total characters3038
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.2%

Sample

1st row#ffffff
2nd row
3rd row
4th row#ffd635
5th row#ff0000
ValueCountFrequency (%)
556
56.2%
#5f9dd294
 
9.5%
#ff000079
 
8.0%
#349e4870
 
7.1%
#ff450045
 
4.5%
#b8001f43
 
4.3%
#cc528926
 
2.6%
#ffb00017
 
1.7%
#ffd63516
 
1.6%
#0079d313
 
1.3%
Other values (8)31
 
3.1%
2021-01-12T21:07:47.773706image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5f9dd294
21.7%
ff000079
18.2%
349e4870
16.1%
ff450045
10.4%
b8001f43
9.9%
cc528926
 
6.0%
ffb00017
 
3.9%
ffd63516
 
3.7%
0079d313
 
3.0%
228b2211
 
2.5%
Other values (7)20
 
4.6%

Most occurring characters

ValueCountFrequency (%)
0581
19.1%
f475
15.6%
#434
14.3%
d220
 
7.2%
9209
 
6.9%
4205
 
6.7%
5182
 
6.0%
2167
 
5.5%
8150
 
4.9%
3116
 
3.8%
Other values (7)299
9.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number1698
55.9%
Lowercase Letter906
29.8%
Other Punctuation434
 
14.3%

Most frequent character per category

ValueCountFrequency (%)
0581
34.2%
9209
 
12.3%
4205
 
12.1%
5182
 
10.7%
2167
 
9.8%
8150
 
8.8%
3116
 
6.8%
145
 
2.7%
722
 
1.3%
621
 
1.2%
ValueCountFrequency (%)
f475
52.4%
d220
24.3%
e78
 
8.6%
b71
 
7.8%
c57
 
6.3%
a5
 
0.6%
ValueCountFrequency (%)
#434
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common2132
70.2%
Latin906
29.8%

Most frequent character per script

ValueCountFrequency (%)
0581
27.3%
#434
20.4%
9209
 
9.8%
4205
 
9.6%
5182
 
8.5%
2167
 
7.8%
8150
 
7.0%
3116
 
5.4%
145
 
2.1%
722
 
1.0%
ValueCountFrequency (%)
f475
52.4%
d220
24.3%
e78
 
8.6%
b71
 
7.8%
c57
 
6.3%
a5
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII3038
100.0%

Most frequent character per block

ValueCountFrequency (%)
0581
19.1%
f475
15.6%
#434
14.3%
d220
 
7.2%
9209
 
6.9%
4205
 
6.7%
5182
 
6.0%
2167
 
5.5%
8150
 
4.9%
3116
 
3.8%
Other values (7)299
9.8%

id
Categorical

UNIQUE

Distinct990
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
ktspuh
 
1
kt6rch
 
1
ksfazj
 
1
krw60y
 
1
kt19l2
 
1
Other values (985)
985 

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters5940
Distinct characters36
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique990 ?
Unique (%)100.0%

Sample

1st rowkv4lr7
2nd rowkvg3xu
3rd rowkv4oca
4th rowkvekkt
5th rowkvfqwa
ValueCountFrequency (%)
ktspuh1
 
0.1%
kt6rch1
 
0.1%
ksfazj1
 
0.1%
krw60y1
 
0.1%
kt19l21
 
0.1%
kuwiyo1
 
0.1%
kqkswb1
 
0.1%
kvekkt1
 
0.1%
kr3bz71
 
0.1%
ku5mq91
 
0.1%
Other values (980)980
99.0%
2021-01-12T21:07:47.985139image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
ktspuh1
 
0.1%
kt6rch1
 
0.1%
ksfazj1
 
0.1%
krw60y1
 
0.1%
kt19l21
 
0.1%
kuwiyo1
 
0.1%
kqkswb1
 
0.1%
kvekkt1
 
0.1%
kr3bz71
 
0.1%
ku5mq91
 
0.1%
Other values (980)980
99.0%

Most occurring characters

ValueCountFrequency (%)
k1097
 
18.5%
r358
 
6.0%
s349
 
5.9%
t293
 
4.9%
u252
 
4.2%
v220
 
3.7%
q168
 
2.8%
y131
 
2.2%
z130
 
2.2%
4128
 
2.2%
Other values (26)2814
47.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4861
81.8%
Decimal Number1079
 
18.2%

Most frequent character per category

ValueCountFrequency (%)
k1097
22.6%
r358
 
7.4%
s349
 
7.2%
t293
 
6.0%
u252
 
5.2%
v220
 
4.5%
q168
 
3.5%
y131
 
2.7%
z130
 
2.7%
f128
 
2.6%
Other values (16)1735
35.7%
ValueCountFrequency (%)
4128
11.9%
5117
10.8%
0114
10.6%
8112
10.4%
1112
10.4%
7110
10.2%
9106
9.8%
3100
9.3%
299
9.2%
681
7.5%

Most occurring scripts

ValueCountFrequency (%)
Latin4861
81.8%
Common1079
 
18.2%

Most frequent character per script

ValueCountFrequency (%)
k1097
22.6%
r358
 
7.4%
s349
 
7.2%
t293
 
6.0%
u252
 
5.2%
v220
 
4.5%
q168
 
3.5%
y131
 
2.7%
z130
 
2.7%
f128
 
2.6%
Other values (16)1735
35.7%
ValueCountFrequency (%)
4128
11.9%
5117
10.8%
0114
10.6%
8112
10.4%
1112
10.4%
7110
10.2%
9106
9.8%
3100
9.3%
299
9.2%
681
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII5940
100.0%

Most frequent character per block

ValueCountFrequency (%)
k1097
 
18.5%
r358
 
6.0%
s349
 
5.9%
t293
 
4.9%
u252
 
4.2%
v220
 
3.7%
q168
 
2.8%
y131
 
2.2%
z130
 
2.2%
4128
 
2.2%
Other values (26)2814
47.4%

is_robot_indexable
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size990.0 B
True
990 
ValueCountFrequency (%)
True990
100.0%
2021-01-12T21:07:48.040996image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

report_reasons
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing990
Missing (%)100.0%
Memory size7.9 KiB

author
Categorical

HIGH CARDINALITY

Distinct526
Distinct (%)53.1%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
Wong_John
 
53
Phatbrew
 
48
DoremusJessup
 
27
progress18
 
21
BlankVerse
 
15
Other values (521)
826 

Length

Max length20
Median length11
Mean length11.34040404
Min length4

Characters and Unicode

Total characters11227
Distinct characters66
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique401 ?
Unique (%)40.5%

Sample

1st rowprogress18
2nd rowmahoneynikki
3rd rowXfiles1987
4th rowPhatbrew
5th rowUploadedMind
ValueCountFrequency (%)
Wong_John53
 
5.4%
Phatbrew48
 
4.8%
DoremusJessup27
 
2.7%
progress1821
 
2.1%
BlankVerse15
 
1.5%
PopuleuxMusicYT15
 
1.5%
Gonzo_B15
 
1.5%
letstalkaboutit2414
 
1.4%
1000000students14
 
1.4%
epc2ky14
 
1.4%
Other values (516)754
76.2%
2021-01-12T21:07:48.238462image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
wong_john53
 
5.4%
phatbrew48
 
4.8%
doremusjessup27
 
2.7%
progress1821
 
2.1%
populeuxmusicyt15
 
1.5%
blankverse15
 
1.5%
gonzo_b15
 
1.5%
epc2ky14
 
1.4%
letstalkaboutit2414
 
1.4%
1000000students14
 
1.4%
Other values (516)754
76.2%

Most occurring characters

ValueCountFrequency (%)
e1040
 
9.3%
a798
 
7.1%
o688
 
6.1%
r620
 
5.5%
n580
 
5.2%
s544
 
4.8%
t527
 
4.7%
i524
 
4.7%
l489
 
4.4%
u334
 
3.0%
Other values (56)5083
45.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter8757
78.0%
Uppercase Letter1282
 
11.4%
Decimal Number956
 
8.5%
Connector Punctuation166
 
1.5%
Dash Punctuation58
 
0.5%
Open Punctuation4
 
< 0.1%
Close Punctuation4
 
< 0.1%

Most frequent character per category

ValueCountFrequency (%)
e1040
 
11.9%
a798
 
9.1%
o688
 
7.9%
r620
 
7.1%
n580
 
6.6%
s544
 
6.2%
t527
 
6.0%
i524
 
6.0%
l489
 
5.6%
u334
 
3.8%
Other values (16)2613
29.8%
ValueCountFrequency (%)
J125
 
9.8%
P101
 
7.9%
B101
 
7.9%
D94
 
7.3%
M88
 
6.9%
W81
 
6.3%
T74
 
5.8%
A68
 
5.3%
S61
 
4.8%
E51
 
4.0%
Other values (16)438
34.2%
ValueCountFrequency (%)
1190
19.9%
0181
18.9%
2111
11.6%
997
10.1%
893
9.7%
772
 
7.5%
460
 
6.3%
558
 
6.1%
355
 
5.8%
639
 
4.1%
ValueCountFrequency (%)
_166
100.0%
ValueCountFrequency (%)
-58
100.0%
ValueCountFrequency (%)
[4
100.0%
ValueCountFrequency (%)
]4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin10039
89.4%
Common1188
 
10.6%

Most frequent character per script

ValueCountFrequency (%)
e1040
 
10.4%
a798
 
7.9%
o688
 
6.9%
r620
 
6.2%
n580
 
5.8%
s544
 
5.4%
t527
 
5.2%
i524
 
5.2%
l489
 
4.9%
u334
 
3.3%
Other values (42)3895
38.8%
ValueCountFrequency (%)
1190
16.0%
0181
15.2%
_166
14.0%
2111
9.3%
997
8.2%
893
7.8%
772
 
6.1%
460
 
5.1%
-58
 
4.9%
558
 
4.9%
Other values (4)102
8.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII11227
100.0%

Most frequent character per block

ValueCountFrequency (%)
e1040
 
9.3%
a798
 
7.1%
o688
 
6.1%
r620
 
5.5%
n580
 
5.2%
s544
 
4.8%
t527
 
4.7%
i524
 
4.7%
l489
 
4.4%
u334
 
3.0%
Other values (56)5083
45.3%

discussion_type
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing990
Missing (%)100.0%
Memory size7.9 KiB

num_comments
Real number (ℝ≥0)

ZEROS

Distinct81
Distinct (%)8.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.32222222
Minimum0
Maximum628
Zeros242
Zeros (%)24.4%
Memory size7.7 KiB
2021-01-12T21:07:48.350260image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q37
95-th percentile40
Maximum628
Range628
Interquartile range (IQR)6

Descriptive statistics

Standard deviation40.43144732
Coefficient of variation (CV)3.570981608
Kurtosis109.0817444
Mean11.32222222
Median Absolute Deviation (MAD)2
Skewness9.311684797
Sum11209
Variance1634.701932
MonotocityNot monotonic
2021-01-12T21:07:48.457973image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0242
24.4%
1169
17.1%
2107
10.8%
374
 
7.5%
449
 
4.9%
547
 
4.7%
630
 
3.0%
730
 
3.0%
924
 
2.4%
819
 
1.9%
Other values (71)199
20.1%
ValueCountFrequency (%)
0242
24.4%
1169
17.1%
2107
10.8%
374
 
7.5%
449
 
4.9%
ValueCountFrequency (%)
6281
0.1%
5451
0.1%
4081
0.1%
3971
0.1%
3161
0.1%
Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size990.0 B
True
922 
False
 
68
ValueCountFrequency (%)
True922
93.1%
False68
 
6.9%
2021-01-12T21:07:48.543340image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

whitelist_status
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
all_ads
980 
promo_adult_nsfw
 
10

Length

Max length16
Median length7
Mean length7.090909091
Min length7

Characters and Unicode

Total characters7020
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowall_ads
2nd rowall_ads
3rd rowall_ads
4th rowall_ads
5th rowall_ads
ValueCountFrequency (%)
all_ads980
99.0%
promo_adult_nsfw10
 
1.0%
2021-01-12T21:07:48.699902image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T21:07:48.756928image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
all_ads980
99.0%
promo_adult_nsfw10
 
1.0%

Most occurring characters

ValueCountFrequency (%)
a1970
28.1%
l1970
28.1%
_1000
14.2%
d990
14.1%
s990
14.1%
o20
 
0.3%
p10
 
0.1%
r10
 
0.1%
m10
 
0.1%
u10
 
0.1%
Other values (4)40
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6020
85.8%
Connector Punctuation1000
 
14.2%

Most frequent character per category

ValueCountFrequency (%)
a1970
32.7%
l1970
32.7%
d990
16.4%
s990
16.4%
o20
 
0.3%
p10
 
0.2%
r10
 
0.2%
m10
 
0.2%
u10
 
0.2%
t10
 
0.2%
Other values (3)30
 
0.5%
ValueCountFrequency (%)
_1000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin6020
85.8%
Common1000
 
14.2%

Most frequent character per script

ValueCountFrequency (%)
a1970
32.7%
l1970
32.7%
d990
16.4%
s990
16.4%
o20
 
0.3%
p10
 
0.2%
r10
 
0.2%
m10
 
0.2%
u10
 
0.2%
t10
 
0.2%
Other values (3)30
 
0.5%
ValueCountFrequency (%)
_1000
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII7020
100.0%

Most frequent character per block

ValueCountFrequency (%)
a1970
28.1%
l1970
28.1%
_1000
14.2%
d990
14.1%
s990
14.1%
o20
 
0.3%
p10
 
0.1%
r10
 
0.1%
m10
 
0.1%
u10
 
0.1%
Other values (4)40
 
0.6%

contest_mode
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size990.0 B
False
990 
ValueCountFrequency (%)
False990
100.0%
2021-01-12T21:07:48.797940image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

mod_reports
Unsupported

REJECTED
UNSUPPORTED

Missing0
Missing (%)0.0%
Memory size7.9 KiB
Distinct1
Distinct (%)0.1%
Missing4
Missing (%)0.4%
Memory size7.7 KiB
False
986 
(Missing)
 
4
ValueCountFrequency (%)
False986
99.6%
(Missing)4
 
0.4%
2021-01-12T21:07:48.825953image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

crosspost_parent
Categorical

MISSING
UNIFORM

Distinct13
Distinct (%)100.0%
Missing977
Missing (%)98.7%
Memory size7.7 KiB
t3_krsf8c
t3_kqx151
t3_kqxf5o
t3_kuewpt
t3_krmvn9
Other values (8)

Length

Max length9
Median length3
Mean length3.078787879
Min length3

Characters and Unicode

Total characters3048
Distinct characters31
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)100.0%

Sample

1st rowt3_kv4jen
2nd rownan
3rd rownan
4th rownan
5th rownan
ValueCountFrequency (%)
t3_krsf8c1
 
0.1%
t3_kqx1511
 
0.1%
t3_kqxf5o1
 
0.1%
t3_kuewpt1
 
0.1%
t3_krmvn91
 
0.1%
t3_kt7y3r1
 
0.1%
t3_ksgyrv1
 
0.1%
t3_krxf5u1
 
0.1%
t3_kqhqxu1
 
0.1%
t3_kv4jen1
 
0.1%
Other values (3)3
 
0.3%
(Missing)977
98.7%
2021-01-12T21:07:48.983093image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nan977
98.7%
t3_krsf8c1
 
0.1%
t3_kqx1511
 
0.1%
t3_kqxf5o1
 
0.1%
t3_kuewpt1
 
0.1%
t3_krmvn91
 
0.1%
t3_kt7y3r1
 
0.1%
t3_ksgyrv1
 
0.1%
t3_krxf5u1
 
0.1%
t3_kqhqxu1
 
0.1%
Other values (4)4
 
0.4%

Most occurring characters

ValueCountFrequency (%)
n1956
64.2%
a977
32.1%
t16
 
0.5%
314
 
0.5%
_13
 
0.4%
k13
 
0.4%
r6
 
0.2%
v5
 
0.2%
f4
 
0.1%
x4
 
0.1%
Other values (21)40
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3006
98.6%
Decimal Number29
 
1.0%
Connector Punctuation13
 
0.4%

Most frequent character per category

ValueCountFrequency (%)
n1956
65.1%
a977
32.5%
t16
 
0.5%
k13
 
0.4%
r6
 
0.2%
v5
 
0.2%
f4
 
0.1%
x4
 
0.1%
q4
 
0.1%
e3
 
0.1%
Other values (12)18
 
0.6%
ValueCountFrequency (%)
314
48.3%
43
 
10.3%
13
 
10.3%
93
 
10.3%
53
 
10.3%
21
 
3.4%
71
 
3.4%
81
 
3.4%
ValueCountFrequency (%)
_13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3006
98.6%
Common42
 
1.4%

Most frequent character per script

ValueCountFrequency (%)
n1956
65.1%
a977
32.5%
t16
 
0.5%
k13
 
0.4%
r6
 
0.2%
v5
 
0.2%
f4
 
0.1%
x4
 
0.1%
q4
 
0.1%
e3
 
0.1%
Other values (12)18
 
0.6%
ValueCountFrequency (%)
314
33.3%
_13
31.0%
43
 
7.1%
13
 
7.1%
93
 
7.1%
53
 
7.1%
21
 
2.4%
71
 
2.4%
81
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII3048
100.0%

Most frequent character per block

ValueCountFrequency (%)
n1956
64.2%
a977
32.1%
t16
 
0.5%
314
 
0.5%
_13
 
0.4%
k13
 
0.4%
r6
 
0.2%
v5
 
0.2%
f4
 
0.1%
x4
 
0.1%
Other values (21)40
 
1.3%

author_flair_text_color
Categorical

MISSING

Distinct1
Distinct (%)10.0%
Missing980
Missing (%)99.0%
Memory size7.7 KiB
dark
10 

Length

Max length4
Median length3
Mean length3.01010101
Min length3

Characters and Unicode

Total characters2980
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rownan
2nd rownan
3rd rownan
4th rownan
5th rownan
ValueCountFrequency (%)
dark10
 
1.0%
(Missing)980
99.0%
2021-01-12T21:07:49.158990image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T21:07:49.218016image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
nan980
99.0%
dark10
 
1.0%

Most occurring characters

ValueCountFrequency (%)
n1960
65.8%
a990
33.2%
d10
 
0.3%
r10
 
0.3%
k10
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2980
100.0%

Most frequent character per category

ValueCountFrequency (%)
n1960
65.8%
a990
33.2%
d10
 
0.3%
r10
 
0.3%
k10
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2980
100.0%

Most frequent character per script

ValueCountFrequency (%)
n1960
65.8%
a990
33.2%
d10
 
0.3%
r10
 
0.3%
k10
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII2980
100.0%

Most frequent character per block

ValueCountFrequency (%)
n1960
65.8%
a990
33.2%
d10
 
0.3%
r10
 
0.3%
k10
 
0.3%

permalink
Path

UNIQUE

Distinct990
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
/r/democrats/comments/kub5f0/follow_me/
 
1
/r/democrats/comments/ktxl87/biden_assembling_multitrilliondollar_stimulus/
 
1
/r/democrats/comments/kq1wdm/impeachable_offence_aoc_wants_to_sanction_trump/
 
1
/r/democrats/comments/kqy084/trump_just_fcked_himself_and_his_party_in_georgia/
 
1
/r/democrats/comments/kr2x00/trump_not_allowed_into_scotland_to_escape_biden/
 
1
Other values (985)
985 

Length

Max length80
Median length74
Mean length67.42929293
Min length31

Characters and Unicode

Total characters66755
Distinct characters38
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique990 ?
Unique (%)100.0%

Sample

1st row/r/democrats/comments/kv4lr7/house_democrats_launch_second_impeachment_of/
2nd row/r/democrats/comments/kvg3xu/do_i_have_to/
3rd row/r/democrats/comments/kv4oca/camp_auschwitz_guy_identified/
4th row/r/democrats/comments/kvekkt/no_crawling_back/
5th row/r/democrats/comments/kvfqwa/use_the_14th_amendment_to_ban_trump/
ValueCountFrequency (%)
/r/democrats/comments/kub5f0/follow_me/1
 
0.1%
/r/democrats/comments/ktxl87/biden_assembling_multitrilliondollar_stimulus/1
 
0.1%
/r/democrats/comments/kq1wdm/impeachable_offence_aoc_wants_to_sanction_trump/1
 
0.1%
/r/democrats/comments/kqy084/trump_just_fcked_himself_and_his_party_in_georgia/1
 
0.1%
/r/democrats/comments/kr2x00/trump_not_allowed_into_scotland_to_escape_biden/1
 
0.1%
/r/democrats/comments/ktbpbk/democratic_attorneys_general_accuse_gop/1
 
0.1%
/r/democrats/comments/kvm1bz/three_new_terrifying_plots_to_overthrow_government/1
 
0.1%
/r/democrats/comments/kt5u9x/how_the_us_capitol_police_were_overrun_in_a/1
 
0.1%
/r/democrats/comments/krolbz/how_georgia_changes_everything_for_joe_biden_and/1
 
0.1%
/r/democrats/comments/krgs5l/jon_ossoff_wins/1
 
0.1%
Other values (980)980
99.0%
2021-01-12T21:07:49.416079image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
r/democrats/comments/krxf8x/biden_condemns_riots_at_capitol_calls_on_trump_to1
 
0.1%
r/democrats/comments/ktjb4f/alex_jones_says_he_paid_500000_for_rally_that_led1
 
0.1%
r/democrats/comments/krxwmh/i_guess_this_aged_like_milk1
 
0.1%
r/democrats/comments/kqrcq8/don_winslow_films_countryovertrump1
 
0.1%
r/democrats/comments/kt5bi2/is_it_possible_to_overdose_on_schadenfreude1
 
0.1%
r/democrats/comments/kuhooy/twitter_congress1
 
0.1%
r/democrats/comments/kudve2/impeach_donald_trump_oc1
 
0.1%
r/democrats/comments/krcryy/ga_voters_that_split_your_ticket_why1
 
0.1%
r/democrats/comments/kti8mc/010620211
 
0.1%
r/democrats/comments/ktbpbk/democratic_attorneys_general_accuse_gop1
 
0.1%
Other values (980)980
99.0%

Most occurring characters

ValueCountFrequency (%)
/5940
 
8.9%
e5591
 
8.4%
_5522
 
8.3%
t5125
 
7.7%
o4590
 
6.9%
s4520
 
6.8%
r4500
 
6.7%
m4099
 
6.1%
a3509
 
5.3%
c3162
 
4.7%
Other values (28)20197
30.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter54017
80.9%
Other Punctuation5940
 
8.9%
Connector Punctuation5522
 
8.3%
Decimal Number1276
 
1.9%

Most frequent character per category

ValueCountFrequency (%)
e5591
10.4%
t5125
 
9.5%
o4590
 
8.5%
s4520
 
8.4%
r4500
 
8.3%
m4099
 
7.6%
a3509
 
6.5%
c3162
 
5.9%
n3073
 
5.7%
i2370
 
4.4%
Other values (16)13478
25.0%
ValueCountFrequency (%)
0185
14.5%
1148
11.6%
4138
10.8%
2138
10.8%
5130
10.2%
7115
9.0%
9115
9.0%
8114
8.9%
3105
8.2%
688
6.9%
ValueCountFrequency (%)
/5940
100.0%
ValueCountFrequency (%)
_5522
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin54017
80.9%
Common12738
 
19.1%

Most frequent character per script

ValueCountFrequency (%)
e5591
10.4%
t5125
 
9.5%
o4590
 
8.5%
s4520
 
8.4%
r4500
 
8.3%
m4099
 
7.6%
a3509
 
6.5%
c3162
 
5.9%
n3073
 
5.7%
i2370
 
4.4%
Other values (16)13478
25.0%
ValueCountFrequency (%)
/5940
46.6%
_5522
43.4%
0185
 
1.5%
1148
 
1.2%
4138
 
1.1%
2138
 
1.1%
5130
 
1.0%
7115
 
0.9%
9115
 
0.9%
8114
 
0.9%
Other values (2)193
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII66755
100.0%

Most frequent character per block

ValueCountFrequency (%)
/5940
 
8.9%
e5591
 
8.4%
_5522
 
8.3%
t5125
 
7.7%
o4590
 
6.9%
s4520
 
6.8%
r4500
 
6.7%
m4099
 
6.1%
a3509
 
5.3%
c3162
 
4.7%
Other values (28)20197
30.3%
Common prefix\r\democrats\comments\k
Unique stems981
Unique names981
Unique extensions1
Unique directories990
Unique anchors1
ValueCountFrequency (%)
/r/democrats/comments/kub5f0/follow_me/1
 
0.1%
/r/democrats/comments/ktxl87/biden_assembling_multitrilliondollar_stimulus/1
 
0.1%
/r/democrats/comments/kq1wdm/impeachable_offence_aoc_wants_to_sanction_trump/1
 
0.1%
/r/democrats/comments/kqy084/trump_just_fcked_himself_and_his_party_in_georgia/1
 
0.1%
/r/democrats/comments/kr2x00/trump_not_allowed_into_scotland_to_escape_biden/1
 
0.1%
/r/democrats/comments/ktbpbk/democratic_attorneys_general_accuse_gop/1
 
0.1%
/r/democrats/comments/kvm1bz/three_new_terrifying_plots_to_overthrow_government/1
 
0.1%
/r/democrats/comments/kt5u9x/how_the_us_capitol_police_were_overrun_in_a/1
 
0.1%
/r/democrats/comments/krolbz/how_georgia_changes_everything_for_joe_biden_and/1
 
0.1%
/r/democrats/comments/krgs5l/jon_ossoff_wins/1
 
0.1%
Other values (980)980
99.0%
ValueCountFrequency (%)
_3
 
0.3%
mustsee_new_video_shows_capitol_riot_was_way2
 
0.2%
we_did_it2
 
0.2%
gop_senator_says_trump_committed_impeachable2
 
0.2%
moscow_mitch_is_now_minority_mitch2
 
0.2%
another_reason_why_we_need_dc_statehood2
 
0.2%
this2
 
0.2%
the_147_republicans_who_voted_to_overturn2
 
0.2%
and_the_winner_is1
 
0.1%
its_this_then1
 
0.1%
Other values (971)971
98.1%
ValueCountFrequency (%)
_3
 
0.3%
mustsee_new_video_shows_capitol_riot_was_way2
 
0.2%
we_did_it2
 
0.2%
gop_senator_says_trump_committed_impeachable2
 
0.2%
moscow_mitch_is_now_minority_mitch2
 
0.2%
another_reason_why_we_need_dc_statehood2
 
0.2%
this2
 
0.2%
the_147_republicans_who_voted_to_overturn2
 
0.2%
and_the_winner_is1
 
0.1%
its_this_then1
 
0.1%
Other values (971)971
98.1%
ValueCountFrequency (%)
990
100.0%
ValueCountFrequency (%)
\r\democrats\comments\kqrcq81
 
0.1%
\r\democrats\comments\kskp121
 
0.1%
\r\democrats\comments\krwlyd1
 
0.1%
\r\democrats\comments\ks2ctb1
 
0.1%
\r\democrats\comments\kujpfh1
 
0.1%
\r\democrats\comments\ks1zwr1
 
0.1%
\r\democrats\comments\ksavgc1
 
0.1%
\r\democrats\comments\kryy9a1
 
0.1%
\r\democrats\comments\krj3f11
 
0.1%
\r\democrats\comments\krdygy1
 
0.1%
Other values (980)980
99.0%
ValueCountFrequency (%)
\990
100.0%

parent_whitelist_status
Categorical

CONSTANT
REJECTED

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
all_ads
990 

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters6930
Distinct characters5
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowall_ads
2nd rowall_ads
3rd rowall_ads
4th rowall_ads
5th rowall_ads
ValueCountFrequency (%)
all_ads990
100.0%
2021-01-12T21:07:49.606766image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T21:07:49.662711image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
all_ads990
100.0%

Most occurring characters

ValueCountFrequency (%)
a1980
28.6%
l1980
28.6%
_990
14.3%
d990
14.3%
s990
14.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5940
85.7%
Connector Punctuation990
 
14.3%

Most frequent character per category

ValueCountFrequency (%)
a1980
33.3%
l1980
33.3%
d990
16.7%
s990
16.7%
ValueCountFrequency (%)
_990
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5940
85.7%
Common990
 
14.3%

Most frequent character per script

ValueCountFrequency (%)
a1980
33.3%
l1980
33.3%
d990
16.7%
s990
16.7%
ValueCountFrequency (%)
_990
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII6930
100.0%

Most frequent character per block

ValueCountFrequency (%)
a1980
28.6%
l1980
28.6%
_990
14.3%
d990
14.3%
s990
14.3%

stickied
Boolean

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size990.0 B
False
989 
True
 
1
ValueCountFrequency (%)
False989
99.9%
True1
 
0.1%
2021-01-12T21:07:49.690730image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

url
Categorical

HIGH CARDINALITY
UNIFORM

Distinct986
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
https://www.bbc.co.uk/news/technology-55569604
 
2
https://www.nytimes.com/interactive/2021/01/07/us/elections/electoral-college-biden-objectors.html
 
2
https://www.theatlantic.com/ideas/archive/2021/01/remove-trump-tonight/617576/
 
2
https://www.cnn.com/2021/01/07/politics/trump-biden-us-capitol-electoral-college-insurrection/index.html
 
2
https://i.redd.it/sq6ala7y27a61.jpg
 
1
Other values (981)
981 

Length

Max length341
Median length35
Mean length64.63636364
Min length22

Characters and Unicode

Total characters63990
Distinct characters73
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique982 ?
Unique (%)99.2%

Sample

1st row/r/JoeBiden/comments/kv4jen/house_democrats_launch_second_impeachment_of/
2nd rowhttps://i.redd.it/sq8b597wpsa61.jpg
3rd rowhttps://i.redd.it/ewmxi3oh0qa61.jpg
4th rowhttps://i.redd.it/863qmtjcbsa61.jpg
5th rowhttps://i.redd.it/nil93j0cmsa61.jpg
ValueCountFrequency (%)
https://www.bbc.co.uk/news/technology-555696042
 
0.2%
https://www.nytimes.com/interactive/2021/01/07/us/elections/electoral-college-biden-objectors.html2
 
0.2%
https://www.theatlantic.com/ideas/archive/2021/01/remove-trump-tonight/617576/2
 
0.2%
https://www.cnn.com/2021/01/07/politics/trump-biden-us-capitol-electoral-college-insurrection/index.html2
 
0.2%
https://i.redd.it/sq6ala7y27a61.jpg1
 
0.1%
https://i.redd.it/webvfod2bx961.png1
 
0.1%
https://np.reddit.com/r/democrats/comments/ksd6uf/congrats_to_georgias_two_new_democratic_senators/?utm_source=share&amp;utm_medium=ios_app&amp;utm_name=iossmf1
 
0.1%
https://www.reddit.com/r/democrats/comments/ks0d4b/small_self_post_its_important_to_realize_that/1
 
0.1%
https://www.huffpost.com/entry/joe-biden-democrats-verge-of-trifecta_n_5ff55a33c5b665581f667eea1
 
0.1%
https://i.redd.it/bc2c328z9t961.jpg1
 
0.1%
Other values (976)976
98.6%
2021-01-12T21:07:49.904072image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.cnn.com/2021/01/07/politics/trump-biden-us-capitol-electoral-college-insurrection/index.html2
 
0.2%
https://www.theatlantic.com/ideas/archive/2021/01/remove-trump-tonight/6175762
 
0.2%
https://www.bbc.co.uk/news/technology-555696042
 
0.2%
https://www.nytimes.com/interactive/2021/01/07/us/elections/electoral-college-biden-objectors.html2
 
0.2%
https://i.redd.it/m5280k0azj961.jpg1
 
0.1%
https://i.redd.it/c89eyzdb80a61.png1
 
0.1%
https://youtu.be/9k49327u4xm1
 
0.1%
https://www.houstonchronicle.com/opinion/editorials/article/editorial-resign-senator-cruz-your-lies-cost-15857293.php1
 
0.1%
https://v.redd.it/mtujnab93ia611
 
0.1%
https://i.redd.it/gatkitroem961.jpg1
 
0.1%
Other values (976)976
98.6%

Most occurring characters

ValueCountFrequency (%)
t5287
 
8.3%
/4396
 
6.9%
e3732
 
5.8%
s3269
 
5.1%
i3186
 
5.0%
o2829
 
4.4%
-2681
 
4.2%
r2655
 
4.1%
a2526
 
3.9%
p2525
 
3.9%
Other values (63)30904
48.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter45667
71.4%
Other Punctuation7928
 
12.4%
Decimal Number6374
 
10.0%
Dash Punctuation2681
 
4.2%
Uppercase Letter668
 
1.0%
Connector Punctuation574
 
0.9%
Math Symbol98
 
0.2%

Most frequent character per category

ValueCountFrequency (%)
t5287
 
11.6%
e3732
 
8.2%
s3269
 
7.2%
i3186
 
7.0%
o2829
 
6.2%
r2655
 
5.8%
a2526
 
5.5%
p2525
 
5.5%
n2169
 
4.7%
d2108
 
4.6%
Other values (16)15381
33.7%
ValueCountFrequency (%)
S43
 
6.4%
C42
 
6.3%
B40
 
6.0%
U35
 
5.2%
P32
 
4.8%
R32
 
4.8%
F32
 
4.8%
I31
 
4.6%
T29
 
4.3%
H28
 
4.2%
Other values (16)324
48.5%
ValueCountFrequency (%)
11260
19.8%
6874
13.7%
0783
12.3%
2733
11.5%
9596
9.4%
5487
 
7.6%
3439
 
6.9%
4423
 
6.6%
7395
 
6.2%
8384
 
6.0%
ValueCountFrequency (%)
/4396
55.4%
.2385
30.1%
:987
 
12.4%
?73
 
0.9%
%32
 
0.4%
&26
 
0.3%
;26
 
0.3%
#3
 
< 0.1%
ValueCountFrequency (%)
_574
100.0%
ValueCountFrequency (%)
-2681
100.0%
ValueCountFrequency (%)
=98
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin46335
72.4%
Common17655
 
27.6%

Most frequent character per script

ValueCountFrequency (%)
t5287
 
11.4%
e3732
 
8.1%
s3269
 
7.1%
i3186
 
6.9%
o2829
 
6.1%
r2655
 
5.7%
a2526
 
5.5%
p2525
 
5.4%
n2169
 
4.7%
d2108
 
4.5%
Other values (42)16049
34.6%
ValueCountFrequency (%)
/4396
24.9%
-2681
15.2%
.2385
13.5%
11260
 
7.1%
:987
 
5.6%
6874
 
5.0%
0783
 
4.4%
2733
 
4.2%
9596
 
3.4%
_574
 
3.3%
Other values (11)2386
13.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII63990
100.0%

Most frequent character per block

ValueCountFrequency (%)
t5287
 
8.3%
/4396
 
6.9%
e3732
 
5.8%
s3269
 
5.1%
i3186
 
5.0%
o2829
 
4.4%
-2681
 
4.2%
r2655
 
4.1%
a2526
 
3.9%
p2525
 
3.9%
Other values (63)30904
48.3%

subreddit_subscribers
Categorical

HIGH CORRELATION

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
175116
418 
175113
224 
175115
199 
175114
149 

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters5940
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row175113
2nd row175113
3rd row175113
4th row175113
5th row175113
ValueCountFrequency (%)
175116418
42.2%
175113224
22.6%
175115199
20.1%
175114149
 
15.1%
2021-01-12T21:07:50.108708image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
2021-01-12T21:07:50.167743image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
175116418
42.2%
175113224
22.6%
175115199
20.1%
175114149
 
15.1%

Most occurring characters

ValueCountFrequency (%)
12970
50.0%
51189
20.0%
7990
 
16.7%
6418
 
7.0%
3224
 
3.8%
4149
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number5940
100.0%

Most frequent character per category

ValueCountFrequency (%)
12970
50.0%
51189
20.0%
7990
 
16.7%
6418
 
7.0%
3224
 
3.8%
4149
 
2.5%

Most occurring scripts

ValueCountFrequency (%)
Common5940
100.0%

Most frequent character per script

ValueCountFrequency (%)
12970
50.0%
51189
20.0%
7990
 
16.7%
6418
 
7.0%
3224
 
3.8%
4149
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII5940
100.0%

Most frequent character per block

ValueCountFrequency (%)
12970
50.0%
51189
20.0%
7990
 
16.7%
6418
 
7.0%
3224
 
3.8%
4149
 
2.5%

created_utc
Real number (ℝ≥0)

HIGH CORRELATION
UNIQUE

Distinct990
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1610089443
Minimum1609685644
Maximum1610433389
Zeros0
Zeros (%)0.0%
Memory size7.7 KiB
2021-01-12T21:07:50.265756image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1609685644
5-th percentile1609815188
Q11609964529
median1610059343
Q31610223065
95-th percentile1610401803
Maximum1610433389
Range747745
Interquartile range (IQR)258535.75

Descriptive statistics

Standard deviation173770.9156
Coefficient of variation (CV)0.00010792625
Kurtosis-0.8019262211
Mean1610089443
Median Absolute Deviation (MAD)108261.5
Skewness0.2728621604
Sum1.593988548 × 1012
Variance3.019633112 × 1010
MonotocityNot monotonic
2021-01-12T21:07:50.380723image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16099586271
 
0.1%
16099500201
 
0.1%
16103779081
 
0.1%
16100661901
 
0.1%
16099072471
 
0.1%
16099570961
 
0.1%
16104278331
 
0.1%
16103823861
 
0.1%
16101605011
 
0.1%
16099479361
 
0.1%
Other values (980)980
99.0%
ValueCountFrequency (%)
16096856441
0.1%
16097074331
0.1%
16097241581
0.1%
16097254651
0.1%
16097344141
0.1%
ValueCountFrequency (%)
16104333891
0.1%
16104321791
0.1%
16104320211
0.1%
16104317431
0.1%
16104310441
0.1%

num_crossposts
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.09191919192
Minimum0
Maximum7
Zeros943
Zeros (%)95.3%
Memory size7.7 KiB
2021-01-12T21:07:50.487589image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.5364710303
Coefficient of variation (CV)5.836333187
Kurtosis74.29531754
Mean0.09191919192
Median Absolute Deviation (MAD)0
Skewness8.06968731
Sum91
Variance0.2878011664
MonotocityNot monotonic
2021-01-12T21:07:50.558400image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0943
95.3%
131
 
3.1%
56
 
0.6%
25
 
0.5%
33
 
0.3%
71
 
0.1%
41
 
0.1%
ValueCountFrequency (%)
0943
95.3%
131
 
3.1%
25
 
0.5%
33
 
0.3%
41
 
0.1%
ValueCountFrequency (%)
71
 
0.1%
56
0.6%
41
 
0.1%
33
0.3%
25
0.5%

media
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing883
Missing (%)89.2%
Memory size7.9 KiB

is_video
Boolean

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size990.0 B
False
987 
True
 
3
ValueCountFrequency (%)
False987
99.7%
True3
 
0.3%
2021-01-12T21:07:50.621234image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

author_cakeday
Boolean

MISSING

Distinct1
Distinct (%)50.0%
Missing988
Missing (%)99.8%
Memory size7.7 KiB
True
 
2
(Missing)
988 
ValueCountFrequency (%)
True2
 
0.2%
(Missing)988
99.8%
2021-01-12T21:07:50.659134image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

is_gallery
Boolean

MISSING

Distinct1
Distinct (%)16.7%
Missing984
Missing (%)99.4%
Memory size7.7 KiB
True
 
6
(Missing)
984 
ValueCountFrequency (%)
True6
 
0.6%
(Missing)984
99.4%
2021-01-12T21:07:50.685063image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

media_metadata
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing983
Missing (%)99.3%
Memory size7.9 KiB

gallery_data
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing984
Missing (%)99.4%
Memory size7.9 KiB

Interactions

2021-01-12T21:07:15.463422image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:15.595070image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:15.710759image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:15.822488image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:15.933192image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:16.042000image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:16.159658image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:16.269393image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:16.387100image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:16.492795image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:16.608485image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:16.756063image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:16.877766image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:16.999439image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:17.120227image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:17.248879image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:17.369657image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:17.498312image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:17.620984image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:17.733682image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:17.854362image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:17.991992image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:18.106685image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:18.221939image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:18.730609image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:18.848294image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:18.971963image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:19.088652image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:19.200325image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:19.320004image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:19.435722image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:19.576318image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:19.693034image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:19.818670image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:19.934388image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:20.057594image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:20.175305image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:20.285014image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:20.403694image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:20.518360image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:20.633081image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:20.770713image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:20.895380image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:21.010078image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:21.134712image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:21.253394image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:21.374071image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:21.504750image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:21.630386image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:21.756077image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:21.882711image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:22.039320image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:22.163522image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:22.300157image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:22.431832image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:22.545501image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:22.665180image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:22.779873image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:22.895565image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:23.010285image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:23.229672image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:23.372528image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:23.498304image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:23.619979image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:23.743621image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:23.878260image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:24.004955image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:24.131610image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:24.257275image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:24.389922image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:24.518548image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:24.682110image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:24.817747image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:24.926158image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:25.051824image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:25.171499image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:25.292177image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:25.411863image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:25.540270image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:25.660945image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:25.789605image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Correlations

2021-01-12T21:07:50.781774image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-01-12T21:07:51.227612image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-01-12T21:07:51.665438image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2021-01-12T21:07:52.097285image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2021-01-12T21:07:26.300278image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:35.074799image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:37.654464image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2021-01-12T21:07:38.391490image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Sample

First rows

approved_at_utcsubredditselftextauthor_fullnamesavedmod_reason_titlegildedclickedtitlelink_flair_richtextsubreddit_name_prefixedhiddenpwlslink_flair_css_classdownsthumbnail_heighttop_awarded_typehide_scorenamequarantinelink_flair_text_colorupvote_ratioauthor_flair_background_colorsubreddit_typeupstotal_awards_receivedmedia_embedthumbnail_widthauthor_flair_template_idis_original_contentuser_reportssecure_mediais_reddit_media_domainis_metacategorysecure_media_embedlink_flair_textcan_mod_postscoreapproved_byauthor_premiumthumbnaileditedauthor_flair_css_classauthor_flair_richtextgildingspost_hintcontent_categoriesis_selfmod_notecrosspost_parent_listcreatedlink_flair_typewlsremoved_by_categorybanned_byauthor_flair_typedomainallow_live_commentsselftext_htmllikessuggested_sortbanned_at_utcurl_overridden_by_destview_countarchivedno_followis_crosspostablepinnedover_18previewall_awardingsawardersmedia_onlylink_flair_template_idcan_gildspoilerlockedauthor_flair_texttreatment_tagsvisitedremoved_bynum_reportsdistinguishedsubreddit_idmod_reason_byremoval_reasonlink_flair_background_coloridis_robot_indexablereport_reasonsauthordiscussion_typenum_commentssend_replieswhitelist_statuscontest_modemod_reportsauthor_patreon_flaircrosspost_parentauthor_flair_text_colorpermalinkparent_whitelist_statusstickiedurlsubreddit_subscriberscreated_utcnum_crosspostsmediais_videoauthor_cakedayis_gallerymedia_metadatagallery_data
0Nonedemocratst2_nkk56FalseNone0FalseHouse Democrats launch second impeachment of Trump for his role in last week's deadly Capitol attack[{'e': 'text', 't': '🔴 Megathread'}]r/democratsFalse60NaNNoneFalset3_kv4lr7Falsedark0.92Nonepublic670{}NaNNoneFalse[]NoneFalseFalseNone{}🔴 MegathreadFalse67NoneTruedefaultFalseNone[]{}linkNoneFalseNone[{'approved_at_utc': None, 'subreddit': 'JoeBiden', 'selftext': 'The House Article of Impeachment will be introduced at 11 a.m. ET today. U.S. House Representatives David Ciciline (D-RI), Ted Lieu (D-CA), and Jamie Raskin (D-MD) are the co-sponsors of the article. #Take action: **[Join us to discuss the second impeachment on Discord](https://discord.gg/ZHaCQ8VFvA)**. House Democrats will charge Trump with "inclement of insurrection" for his role in last week’s deadly Capitol attack. A draft of the resolution states: &gt; **ARTICLE 1: INCITEMENT OF INSURRECTION** &gt; ...In his conduct of the President of the United States—and in violation of his constitutional oath faithfully to execute the offie of President of the United States and, to the best of his ability, preserve, protect, and defend the Constitution of the United States, and in violation of his constitutional duty to take care that the laws be faithfully executed—Donald John Trump engaged in high Crimes and Misdemeanors by willfully inciting violence against the Government of the United States… **Live Updates** * CNN: [Live updates](https://www.cnn.com/politics/live-news/trump-impeachment-news-01-11-21/index.html) **Live Streams** * [NBC News NOW](https://www.youtube.com/watch?v=BVqm9JnKHZM) * [ABC News Live](https://www.youtube.com/watch?v=w_Ma8oQLmSM) * [C-SPAN](https://www.c-span.org/video/?507803-1/house-expected-introduce-article-impeachment-president-trump) * [PBS NewsHour](https://www.youtube.com/watch?v=i35nRKxOtVQ&amp;) * *More live streams will be added in this section once they go live* *Use the report button to report any trolls.*', 'author_fullname': 't2_nkk56', 'saved': False, 'mod_reason_title': None, 'gilded': 0, 'clicked': False, 'title': 'House Democrats launch second impeachment of Trump for his role in last week’s deadly Capitol attack', 'link_flair_richtext': [{'e': 'text', 't': '🔴 Megathread'}], 'subreddit_name_prefixed': 'r/JoeBiden', 'hidden': False, 'pwls': 7, 'link_flair_css_class': '', 'downs': 0, 'thumbnail_height': None, 'top_awarded_type': None, 'hide_score': False, 'name': 't3_kv4jen', 'quarantine': False, 'link_flair_text_color': 'dark', 'upvote_ratio': 0.98, 'author_flair_background_color': '', 'subreddit_type': 'public', 'ups': 203, 'total_awards_received': 0, 'media_embed': {}, 'thumbnail_width': None, 'author_flair_template_id': None, 'is_original_content': False, 'user_reports': [], 'secure_media': None, 'is_reddit_media_domain': False, 'is_meta': False, 'category': None, 'secure_media_embed': {}, 'link_flair_text': '🔴 Megathread', 'can_mod_post': False, 'score': 203, 'approved_by': None, 'author_premium': True, 'thumbnail': 'self', 'edited': 1610382383.0, 'author_flair_css_class': '', 'author_flair_richtext': [], 'gildings': {}, 'post_hint': 'self', 'content_categories': None, 'is_self': True, 'mod_note': None, 'created': 1610406838.0, 'link_flair_type': 'richtext', 'wls': 7, 'removed_by_category': None, 'banned_by': None, 'author_flair_type': 'text', 'domain': 'self.JoeBiden', 'allow_live_comments': True, 'selftext_html': '&lt;!-- SC_OFF --&gt;&lt;div class="md"&gt;&lt;p&gt;The House Article of Impeachment will be introduced at 11 a.m. ET today. &lt;/p&gt; &lt;p&gt;U.S. House Representatives David Ciciline (D-RI), Ted Lieu (D-CA), and Jamie Raskin (D-MD) are the co-sponsors of the article.&lt;/p&gt; &lt;h1&gt;Take action: &lt;strong&gt;&lt;a href="https://discord.gg/ZHaCQ8VFvA"&gt;Join us to discuss the second impeachment on Discord&lt;/a&gt;&lt;/strong&gt;.&lt;/h1&gt; &lt;p&gt;House Democrats will charge Trump with &amp;quot;inclement of insurrection&amp;quot; for his role in last week’s deadly Capitol attack.&lt;/p&gt; &lt;p&gt;A draft of the resolution states: &lt;/p&gt; &lt;blockquote&gt; &lt;p&gt;&lt;strong&gt;ARTICLE 1: INCITEMENT OF INSURRECTION&lt;/strong&gt;&lt;/p&gt; &lt;p&gt;...In his conduct of the President of the United States—and in violation of his constitutional oath faithfully to execute the offie of President of the United States and, to the best of his ability, preserve, protect, and defend the Constitution of the United States, and in violation of his constitutional duty to take care that the laws be faithfully executed—Donald John Trump engaged in high Crimes and Misdemeanors by willfully inciting violence against the Government of the United States…&lt;/p&gt; &lt;/blockquote&gt; &lt;p&gt;&lt;strong&gt;Live Updates&lt;/strong&gt;&lt;/p&gt; &lt;ul&gt; &lt;li&gt;CNN: &lt;a href="https://www.cnn.com/politics/live-news/trump-impeachment-news-01-11-21/index.html"&gt;Live updates&lt;/a&gt;&lt;/li&gt; &lt;/ul&gt; &lt;p&gt;&lt;strong&gt;Live Streams&lt;/strong&gt;&lt;/p&gt; &lt;ul&gt; &lt;li&gt;&lt;a href="https://www.youtube.com/watch?v=BVqm9JnKHZM"&gt;NBC News NOW&lt;/a&gt;&lt;/li&gt; &lt;li&gt;&lt;a href="https://www.youtube.com/watch?v=w_Ma8oQLmSM"&gt;ABC News Live&lt;/a&gt;&lt;/li&gt; &lt;li&gt;&lt;a href="https://www.c-span.org/video/?507803-1/house-expected-introduce-article-impeachment-president-trump"&gt;C-SPAN&lt;/a&gt;&lt;/li&gt; &lt;li&gt;&lt;a href="https://www.youtube.com/watch?v=i35nRKxOtVQ&amp;amp;"&gt;PBS NewsHour&lt;/a&gt;&lt;/li&gt; &lt;li&gt;&lt;em&gt;More live streams will be added in this section once they go live&lt;/em&gt;&lt;/li&gt; &lt;/ul&gt; &lt;p&gt;&lt;em&gt;Use the report button to report any trolls.&lt;/em&gt;&lt;/p&gt; 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